(BQ) Part 1 book Elementary statistics has contents Statistics, descriptive analysis and presentation of single variable data, descriptive analysis and presentation of bivariate data, probability, probability distributions (discrete variables), normal probability distributions, sample variability.
Trang 2Cherry orchard yields: 9.155
Circumferences of oranges: 9.149
Corrosive effects of soil: 10.27
Diameters of Red Delicious apples: 7.50, 7.51
Diameters of tomatoes: 9.180
Farm real estate values: 9.139
Germination trials: 5.123, 5.124
Grapefruit characteristics: 4.147, CPT 8.15
Growth of hybrid plants by soil type: CPT 11.14
Magnesium and calcium in Russian wild rye: 13.77
Maturity time of green beans: 9.138
Nitrogen fertilizer and wheat production: 13.85,
CPT 13.11, CPT 13.12, CPT 13.13, CPT 13.14,
CPT 13.15, CPT 13.16, CPT 13.17, CPT 13.18,
CPT 13.19, CPT 13.20, CPT 13.21
Number of stamens and carpels in flowers: 13.83
Oat crop yields: 9.158, 10.162, 12.28
Peanut yield rate: 14.6, 14.36
Petal and sepal measurements of irises: 3.27
Petal width of irises: 12.53
Strontium distribution coefficient and total aluminum
Weight gains for chicks: 2.157
Weight gains for pigs: 10.20
Weights of poultry flock: 9.27
Wheat production: 13.1, 13.2, 13.91
World cocoa production: 2.16
Yields of hops: 2.109
Biological Science
Animals’ brain lengths and weights: 13.22
Brown trout lengths: 2.191
Cayuga Lake fish lengths: 8.35
Cricket chirp rate and temperature: 3.96
Distribution and abundance of sea otters: AEx 14.8
Lake trout lengths: CPT 7.11
Length and age of blacknose dace: 3.94
Length and weight of alligators: 3.98
Length and weight of bears: 13.6
Lengths of hatchery-raised trout: 8.173
Long-haired rabbits: 5.70
Manatee deaths in Florida: 3.37, 11.31
Mendelian theory of inheritance: Ex 11.2, 11.12, 11.13,
11.15, 11.47
Nutrient loads discharged into Biscayne Bay: AEx 13.11,
13.66
Shark attacks: AEx 1.4
Weight and girth of horses: 13.12
Weight and length of adult cicadas: 3.101, 12.54, 13.64
Weight gain of laboratory mice: 10.71, CPT 14.12
Weights of bees’ loads of pollen and nectar: 8.183
Business, Economics, and Financial Management
Accuracy of tax withholding: 11.50
Ages and prices of Honda Accords: 3.72
American Express card fees: 6.111
Amounts in medical flexible spending accounts: 8.150
Amounts spent on veterinary care: 7.52
Annual fuel consumption: 8.187
Auto repair charges: 8.87, 10.10
Average home size: 8.116
Best companies to work for: 5.7
Burden of proof in tax dispute cases: 10.157
Carat weight and price of diamonds: 13.45
Company dress codes: 2.5
Company spending on travel: 3.4
Compensation by type of organization: 1.4
Costs of luxury cars and “feel alike” models: 3.70
County transfer taxes: 12.46
Credit card rewards and rebates: 9.77
Customer accounts at banks: 9.72
Delivery service fees: 2.25
Earnings per share for banking industry: 2.186
Earnings per share for radio industry: 2.223
Emergency funds available by gender: 3.82
Entertainment sports industry salaries: 4.65
Executive salaries: 6.46
Executives’ job search: 1.72
Expected payoff from investment: 5.125
Franchised restaurant sales: 9.179
Gas-tax money by region: 12.44
GDP and level of technology: 13.20
Gold-collar workers: 6.50
Home values in college town: 9.48 Home values in Rochester suburbs: 10.73 Hourly earnings by industry: 2.196 Hourly wages of production workers: 12.35 Hours worked by Java professionals: 1.3 House selling prices: 2.18, 10.62 Illegal tax deductions: 4.75 Jeans inventories in Levi Strauss stores: 9.49 Job growth percentage changes: 14.83 Job interview outcomes: 4.149 Leasable office space available: 6.62 Life insurance purchases: 4.113 Life insurance rates: AEx 3.6, 3.49, 3.75, Ex 4.6 Losses from online identity theft: 8.166 Magazine subscription rates: 3.35 Making business decisions: 4.119 Minimum deposit and interest rate: 3.10 Monthly car payments: 2.222 Mortgage foreclosures: 5.75 Motor-fuel taxes: 3.65 Number of client contacts and sales volume: 13.41 Numbers of automobiles by country: 4.143 Obesity and productivity: AEx 1.3
“On-hold” times for customer service: 6.61 Opinions on fringe benefits by gender: 4.156 Prices of laptop computers: 8.113 Property damage in automobile accidents: 4.152 Reducing debt: 11.21
Resale price and age of luxury autos: 3.63 Revenue per kilowatt-hour in Arkansas: 2.47 Salaries of clerk-typists: 8.186
Salaries of elementary school teachers: 2.107 Salaries of human resources clerks: 6.48 Salaries of junior executives: Ex 6.14 Salaries of labor relation managers: 7.38 Salaries of machine shop employees: CPT 2.16 Salaries of registered nurses: 7.42, 7.49 Salaries of resort club managers: 2.39, 2.51 Sales potential ranking and sales totals: CPT 14.13 Savings account amounts: 7.59
Service contractor complaints: AEx 2.17, 2.150 Spa industry profits: AEx 1.2, 1.7
Taxes per capita: 2.81, 2.85 Tax refunds: 1.11 Times to settle insurance claims: 9.103 Total personal income and value of new housing units:
13.39 Total returns in banking industry: 2.24 Turnover among nurse executives: 10.83 Unemployment rates: 3.9, 6.131 Unit pricing: 1.37
Used-car inventory: Ex 4.4 Values of funded projects: 8.15 Waiting time in post office: CPT 8.11, CPT 9.18 Yum Brands abroad: 4.53
College Life
Absences at 8 AM classes: 14.49, 14.72 ACT composite score and first-term college GPA: 13.5 Amount of trash discarded by students: 9.34 Budgeting for intramural and interscholastic sports: 9.73 Caffeine consumption: 9.50
Cars driven by students: Ex 9.8, Ex 9.13, 9.69 Cars owned by college faculty: Ex 1.5 Chemistry students by gender: 9.106 College applications: 5.21 Commute times: CPT 6.15, 9.47 Commute times and distances: 3.22 Commuting distance: 2.141, Ex 8.2, 8.124 Concrete Canoe Competition: 2.66 Cornell’s tuition and ranking: AEx 2.16, 2.149 Cost of textbooks: 1.26, Ex 1.8, 8.180, 9.25, 9.152, 9.153 Course selection criteria: 11.40
Cultural literacy of college freshmen: 12.22 Dropout rate: 6.94
Electronic study guides for accounting principles: 10.63 Final averages: 6.57
Final exam scores by teaching method: CPT 10.14 Genders and majors: Ex 3.1
GPAs and membership in fraternal organizations:
Ex 10.9 Graduation rates: 4.123 Guessing on multiple-choice tests: 5.126 Hours of sleep: 2.70, 2.93, 6.39, 9.54 Hours worked per week: Ex 14.5 Introductory psychology course grades: 11.46 Living at home after graduation: 9.167 Mathematics placement exam scores: 10.50, 10.151 Monthly debt after college graduation: 2.54, 2.168 Number of colleges applied to: AEx 5.3 Number of credit hours: 2.217 Paying off college debt: 2.174 Preference for liberal arts courses by gender: Ex 11.5 Preferences for math course sections: Ex 11.1 Professor late for class: 4.163
Salaries of full professors in Colorado: 14.16 Scholarship applications: 4.118
Statistics final exam scores: Ex 2.6, Ex 2.12, Ex 2.13, 2.105, Ex 2.19
Statistics pass rates: 4.41 Student characteristics: 1.67 Student credit card debt: 10.1, 10.2, 10.164 Student-owned vehicle makes: 2.8 Students’ places of residence: 11.49 Summer schedule: 1.23, 4.52 Test scores: 9.55
Tuition and fees: 8.42, 10.70 Undergraduate GPA and GPA at graduation: 14.61 Weight of books and supplies: 1.24
Demographics and Population Characteristics
Age and gender of licensed drivers: 4.136 Age at marriage: 7.56
Ages of auto theft offenders: 2.183 Ages of dancers: 2.36
Ages of D.C residents: 2.9, 4.134 Ages of fishermen: 2.162 Ages of heads of household: 2.220 Ages of licensed drivers: 6.49 Ages of NASCAR drivers: 2.71, 2.94 Ages of New York population: 2.169, 2.176 Ages of night-school students: 8.34 Ages of nuns: 2.42, 2.166 Ages of U.S population: 2.165, 4.155 Area (sq mi.) of U.S states: 2.193 Baby birth days: AEx 11.3, 11.22 Baby birth months: 11.52 Birth weights for babies in U.S.: 8.114 Census data: AEx 1.6, 7.1, 7.2, 7.67, 7.68 College attendance in suburban populations: 2.48 Divorce rates: 1.12
Genders of licensed drivers: 6.95 Grandparents as primary caregivers: 4.117 Gray hair by gender: 10.158
Handedness: 4.66 Height and age of children: 3.17 Height and shoe size: 3.2, 13.72 Height and weight of college women: Ex 3.7, 3.69 Heights and weights of professional soccer team: 3.26 Heights and weights of World Cup players: 3.12, 3.18 Heights of college students: Ex 10.8
Heights of high-school football players: 2.143 Heights of kindergartners: Ex 7.6, Ex 7.7, 7.32, 7.37, 7.43
Heights of male college students: 7.35 Heights of mothers and daughters: 3.11 Heights of NBA players: 2.19, 12.24 Heights of Olympic soccer players: 2.33 Heights of women in health profession: 8.199 High-poverty neighborhood populations: 2.55 Homeownership rates: 11.59
Household incomes: AEx 2.11, 4.11, 14.48 Increases in U.S population by area: 2.26, 2.142 Life expectancies by gender: 3.95
Monroe Community College demographics: 4.142 Montana’s household population: 2.6 Number of children adopted: 3.44 Number of children fathered by doctors: 2.156 Number of children per family: 5.19 Number of licensed drivers: 1.75, 2.79, 3.24 Number of people per household: 2.34 Number of push-ups and sit-ups: Ex 3.3, Ex 3.5, 3.62 Number of rooms in Texas housing units: 2.35 Number of students by grade level: 1.8 Number of telephones per household: 2.153 Number of televisions in American households: 7.22 Number of televisions in Japanese households: 5.104 Number of years of college of high-tech employees: 8.47 Ophthalmic trait and eye color: 4.154
Percentages in service and trade job categories: 14.63 Political preference by age: 11.61
Poverty and life expectancy: 3.54 Vehicle registrations and population: 3.79 Vehicles per household: 2.80, 4.115, 5.34, 5.106 Weights of adult males: 9.51, 9.52, 11.53 Weights of college students: Ex 2.5 Weights of college women: 8.82, Ex 8.21 Weights of high-school football players: 2.144 Weights of second-grade boys: Ex 8.6 Weights of 10-year-old girls: 8.184
Education and Child Development
ACT exam takers: 2.195 ACT scores: 2.106, 2.126, 2.140, 2.202, 6.52, 6.109 Age at first dental exam: 2.155
AP test results: 2.32, 2.52 Attitudes of preschoolers’ parents: 1.70 Composition exam scores: CPT 9.13 Computer science aptitude test scores: 2.41, 2.53, 10.142, 13.46, 13.50
Content title and reading comprehension: 10.28 Costs of baby supplies: 2.172
Costs of day care: 6.47 Daily activities of schoolchildren: 5.11 Effects of social skills training: 12.61
Ex: Example; AEx: Applied Example; CPT: Chapter Practice Test.
All others are exercises.
Trang 3Examination scores: Ex 2.3, Ex 2.4, 6.117, 14.71
Grade comparison for blondes and brunettes: 10.65
Hours of work per week by high-school juniors and
seniors: 10.66
Hours studied for exam and grade received: 3.15, 3.19,
3.33, 3.38, 3.58, 13.48, 13.51, 13.52
Imaginary friends and coping skills: 9.76
Inherited characteristics of twins: AEx 10.3
Instructional time in social studies: 1.73
International Mathematics and Science Study results for
Mastery of basic math by high-school seniors: 14.21
Methods of teaching reading: 12.48
Minimum score required for grade of A: Ex 6.12
Misbehaving and smoking: 5.63
Mothers’ use of personal pronouns when talking with
Order of finish and scores on exams: Ex 14.14
Parental concerns in choosing a college: 10.100
Physical fitness classes: Ex 10.1
Poverty and proficiency tests: AEx 3.4, 3.16, 3.21, 3.34
Prefinal average and final exam score: 13.84
Proficiency test scores for Ohio fourth-graders: 14.32
Reading proficiency test scores for sixth-graders: 14.7,
14.14
SAT scores: 2.164, CPT 6.16
Social skills in kindergarten: AEx 1.1, AEx 1.9
Standard scores for exam grades: Ex 2.14, 2.122
Strength test scores of third-graders: 2.45, 2.75
Student computer access by grade level: AEx 12.4, 12.9
Summer jobs for high-schoolers: 5.10
TIMSS scores: 7.40, 8.37
Truancy counseling: CPT 10.21
Variability of exam scores: 1.39, 9.176
Wearing of protective clothing by teens: 14.15
Leisure and Popular Culture
Ages of thoroughbred racing fans: 8.151
American Kennel Club registrations by breed: 3.83
Amounts spent on high school prom: 7.41
Aquarium inhabitants: 4.96
Art museum scheduling: 4.165
Asymmetry of euro for coin tossing: AEx 9.14
Blog creators and readers: 11.39
Carnival game probabilities: 4.77, 4.78
Casino gaming rules: AEx 14.12
Cell phone distractions while driving: 1.10
Cell phone text messaging: 9.175
Coffee break: 4.76
Contract bridge hands: 4.45
Cooling mouth after a hot taste: 11.1, 11.2, 11.69
Dimensions and base price of jet boats: 13.57
Dog-obedience training techniques: Ex 14.7
Dog ownership: 4.59, 5.20, 5.36
Downloading music and video files: 6.96
Downloading with cell phones: AEx 11.4, 11.8
Expenditures on leisure activities: 10.60
Halloween candy: 5.80
Help with household chores: 2.13
Hours of housework for men: 7.54
Hours of sleep on weekend: Ex 9.12, 10.128
Hours of television watching: 2.184, 7.23, 14.4
Hours spent housecleaning: AEx 2.7
Impact of Internet on daily life: 5.64
Instant messaging: 6.128
Internet usage: 2.1, 2.2, 2.212, 2.224, 5.79, 9.165
Length of visit to library home page: 8.50
Lengths of pop-music records: 7.62, 7.63
Lottery tickets: 5.113
Lower-leg injuries in skiing: CPT 13.22
M&M colors: 2.197, 4.1, 4.2, 4.3, 4.170, 4.171, 11.57
Misplacements of TV remote control: 2.119
Mother’s Day expenses: 8.117
Number of rolls of film dropped off for developing: 12.32
Number of TV sports reports watched per week: 2.167
Obtaining “comfort food”: 11.54, 11.55, 11.56
Personal watercraft accidents: 9.108
Powerball Lottery game: CPT 4.20
Probability of winning carnival game: Ex 4.13
Rankings of contest participants: Ex 14.13
Rebound heights of table-tennis balls: 14.80
Restaurant wait times: 8.164
Rifle-shooting competition scores: 10.136, 10.141
Shooting accuracy by method of sighting: Ex 12.6
Skittles colors: 11.23, 11.24
Spring cleaning survey: 1.9
Stamp collection value: 8.16
Swimming lessons: 4.10, 4.50, 4.97
Television ratings: 4.29, 4.49
Times for haircuts: 2.206
Time off during holidays: 1.78
Time spent in video games by children: 14.46
Valentine’s Day: 2.12, 2.148, 10.129
“Wired” senior citizens: 5.111
Manufacturing and Industry
Absenteeism rates of employees: 11.66 Accuracy of wristwatches: 8.119 Air bag design: Ex 8.8 Amount of force needed to elicit response: 10.163 Amounts of fill: 1.38, 6.53, 6.115, 6.118, 8.194, Ex 9.17,
Ex 10.10, Ex 10.15, Ex 10.17, 10.160, 12.45 Asphalt mixtures: 8.58
Asphalt sampling procedures: AEx 10.7, 10.37 Bad eggs: Ex 5.9
Breaking strength of rope: 8.182 Breaking strengths of steel bars: 7.55 Cellular phone defects: Ex 10.13 Charges for home service call by plumbers: 8.129 Comparing production methods: 10.101, 11.44 Comparing reliability of microcomputers: 10.153 Concrete shrinkage and water content: AEx 3.8 Cork characteristics: AEx 6.15, 8.79, 8.80 Cost per unit and number of units produced per manu- facturing run: 3.64
Crew clean-up time: 2.133 Defective bolts: Ex 9.11 Defective parts: 3.85, 4.27, 4.48, 4.67, 4.122, Ex 4.26, 5.67, 9.168, 10.87, 11.37, 14.81
Defective products: 2.15 Defective rifle firing pins: Ex 6.19 Defective television sets: Ex 5.7 Defects in garments: 2.11 Delay times for sprinkler systems: 8.179 Delivery truck capacity: 7.61 Detonating systems for explosives: 8.51, 8.62 Diameter and shear strength of spot weld: 13.58 Diameters of ball bearings: 8.181
Diameters of wine corks: 6.55, 9.60 Drying time for paint: Ex 8.9, Ex 8.14, 8.88, 9.28 Dry weights of corks: 9.141
Effect of heat treatment of length of steel bar: 10.48 Effect of temperature on production level: Ex 12.1, 12.3 Extraction force for wine corks: 6.54, 8.41, 9.182 Failure torque of screws: 9.24
Fill weights of containers: 6.60, 7.36 Flashlight battery lifetimes: CPT6.14, 7.44 Hours worked by production workers: 12.52 Lawn mower warranties: 6.125
Lengths of commutators: 2.21, 9.58 Lengths of lunch breaks: 9.26 Lengths of machined parts: 8.33, 8.39 Lengths of nails: 9.181
Lengths of power door brackets: 2.204 Lengths of wine corks: 9.61 Lens dimensions: 2.72, 6.134, 6.135, 9.150, 10.22, 10.38, 10.74, 10.127, 12.49, 13.60, 13.61, 13.62
Lifetime mileage of tires: 2.132 Lifetimes of cigarette lighters: CPT 7.12 Lifetimes of light bulbs: 2.221, 6.116, 7.57, CPT 8.16, 9.177
Light bulb failures: 5.98 Luxury car colors: 4.56 Machine downtimes: 14.47 Maintenance expenditures for television sets: 9.154 Mileage of automobile tires: 7.58
Mileage of service truck tires: 9.147 Mislabeled shoes: 4.132 Net weights of bags of M&Ms: 6.63 Nutrition information and cost for sports drinks: 3.43, 3.59
Nutrition information for frozen dinners: 8.127 Nutrition information for hot dogs: 2.76 Nutrition information for peanut butter: 12.39 Nutrition information for soups: 2.205, 14.60 Octane ratings of gasoline: 2.182, 9.56 Online queries to PC manufacturers: 11.18 Ovality of wine corks: 8.168
Paint drying time: 2.181 Parachute inspections: 8.56 Particle size of latex paints: 2.203, Ex 8.3, 10.9 Particulate emission in generation of electricity:
CPT 12.14 Performance of detergents: Ex 8.10, Ex 8.12 Product assembly times by gender: 10.159 Proofreading errors: 4.166
Quality control: 1.27, 5.72, 5.119, 7.3 Refrigerator lifetime: 6.114 Rivet strength: 8.81, 8.123 Salvaged tires: 4.151 Screw torque removal measurements: 10.149 Service provided by PC manufacturers: 10.96 Shearing strength of rivets: 6.112, CPT 7.13 Strength and “fineness” of cotton fibers: 13.68 Strength intensity of a signal: 10.135 Sulfur dioxide emissions: Ex 8.19 Temperature of ovens during baking process: 10.119 Tensile strength of cotton fibers: 10.125
Testing rivets: 8.85, 8.128 Test-scoring machine accuracy: 6.124 Thread variance in SUV lug nuts: 10.161
Tread wear of tires: 8.190, Ex 10.4, Ex 10.6 T-shirt quality control: 5.47, 5.97, CPT 5.12 Union membership: 4.28, 6.100 Union membership and wages: 4.68 Units of work completed per day: 12.25 Variability of package weights: 9.136 Variability of weightlifting plates: 9.137 Variation in lengths of produced parts: 9.178 Wearing quality of auto tires: Ex 10.2 Weights of bread loaves: 7.34 Weights of cereal boxes: 8.163, 9.183, 9.184, 9.185 Weights of cheese wheels: 10.61
Weights of mini-laptop computers: 8.49 Weights of “1-pound” boxes: 2.161 Weights of packages shipped by air: 8.154 Weights of “10-pound” bags of potatoes: 10.64 Worker satisfaction: 4.131
Marketing and Consumer Behavior
Amount spent by customers: CPT 8.17 Apple-eating preferences: 2.4 Assessing demand for new product: 1.46 Automobile brands of GM employees: 5.50 Baked potato preferences: AEx 11.7, 11.38, 11.45 Blind taste tests for cola preference: 14.19 Bottled water consumption: 6.51 Burger condiments: 9.70 Burger consumption: 9.160 Caffeine consumption: 5.1, 5.2, 5.128, 5.129 Chocolate-covered candy bar preferences: 14.74 Christmas tree sales: 2.194
Coffee drinking trends: 6.129 Coffee preferences of married men: 9.161 Consumer fraud complaints: 5.62 Customer preferences for seating arrangements in restaurants: CPT 14.19
Deodorant soap preferences: 10.88 Easter candy purchases: 4.124 Effectiveness of different types of advertisements: 12.26 Effectiveness of television commercials: 8.66, 8.67 Effect of sales display location on sales: 12.40 Features desired by home buyers: 14.64 Floor polish preferences: 11.14 Gasoline purchases by method of payment: 3.8 German restaurant ratings: 12.27
Grocery shopping habits: 1.69 Ground beef preferences: 11.17 Holiday shopping preferences: 2.151
“More space” preferences of leisure travelers: 3.3 Movie budgets, box office receipts, and Oscar nomina- tions: 3.46
Nielsen ratings and number of viewers: 3.78 Number of commercials and sales of product: 3.40 Number of customers during noon hour: CPT 2.15 Number of customers per day: 7.53
Number of items purchased: CPT 2.12 Outdoor features desired in new homes: 5.23 Pizza crust preferences: 9.171, 9.172, 9.173, 14.20 Popcorn brand preferences: 11.63
Portuguese wine ratings and prices: 13.23 Price comparisons among grocery stores: 12.41 Product endorsements by athletes: 9.162 Radio hits: 5.112, 11.58
Radio station format preferences over time: 14.86 Ratings and street price ranks of computer monitors: 14.57
Readership of Vogue magazine: 5.108
Restaurant decor rating and cost of dinner: 13.35 Retail store customer data: 12.36, 12.37, 12.38, 12.55, 12.56, 12.57, 13.69, 13.70, 13.71, 13.86, 13.87 Satisfaction with auto service departments: 9.163 Spousal preferences for television programs: 14.84 Television brand ratings: 4.153
Turkey consumption: 7.25 Use of cleaning wipes: 2.10
Medical Science
Abnormal male children and maternal age: 9.157 Acetaminophen content of cold tablets: 9.59 Acute back pain treatments: 10.147 Adverse drug reactions: 9.81, 9.82 Allergies in adults: 1.15 Amount of general anesthetic: 10.137 Amounts of water consumed daily: 8.155, 8.156 Amounts spent on prescription drugs: 9.23 Angina: 10.68
Anticoagulants and bone marrow transplantation: 14.18 Benefits of exercise: 9.1, 9.2, 9.187, 9.188
Blood pressure readings: 10.122 Blood types: 11.48
Body Mass Index (BMI) scores: 8.120, 14.70 Caffeine and dehydration: 9.71
Calculus or tartar: AEx 14.15 Cancer testing: 4.158 Carpal tunnel syndrome: 2.163 Causes of death in United States: 2.175 Cholesterol readings: 10.17, 10.30, 14.34 Clinical trials: 11.43
Clotting time and plasma heparin concentrations: AEx 13.4
Comparing methods of cataract surgery: 14.33
Trang 4Diastolic blood pressure readings: 10.47
Effect of calcium channel blockers on pulse rate: Ex 10.5
Effect of diet on uric acid level: 10.8
Effect of drug in lowering heart rate: 13.67
Effects of biofeedback and relaxation on blood pressure:
Health benefits of exercise: 1.45
Health status of older Americans: 1.79
Hemoglobin test for diabetic patients: 2.44
Hip-replacement surgery: 5.105
Hospital stays after surgery: 12.21
Hypertension: 1.25
Immediate-release vs sustained-release codeine: 10.138
Infant mortality rates: 2.108, 6.133
Injury severity in younger and older children: 10.120
Length of pain relief: 12.42
Life expectancy: 1.80
Lung cancer and smoking: 4.26
Lung cancer survival rate: 9.90
Manual dexterity scores: 2.110
Marriage and health status: 1.74
Maternal death rates: 4.46
Medical assistance for accident victims: 8.57
Melanoma survival rates: 6.93
Methods for teaching anatomy: AEx 10.11, 10.67, 14.77
Mineral concentration in tissue samples: 14.59
Noise level in hospitals: CPT 8.18
Organ donation: 11.65
Percentages of nicotine in cigarettes: 14.30
“Persistent disagreements” in therapeutic recreation:
2.118
Plasma concentration of ranitidine: 13.78
Plasma protein binding of diazepam: 12.60
Prescription drug use: 1.81
Prescription drug use by seniors: 9.170
Pulse rates: 9.29, 9.30, 14.31
Response time to blood pressure medication: 8.171
Salt-free diets and diastolic blood pressure: 10.19
Self-care test scores of recently diagnosed diabetics:
10.29
Side effects of drugs: 1.22, 1.29, 5.107, 10.102
Sleep apnea: 4.60
Substance abuse: 1.82, 6.99
Survival rate during surgery: 5.66
Testing effectiveness of new drugs: 8.195, 8.196
Time since last doctor visit by age: 3.84
Wait time for urgent care: 9.146
Weight loss on no-exercise plan: Ex 14.3
Weights before and after smoking cessation: CPT 10.15,
CPT 14.11
Weights of newborns: Ex 9.4
Physical Sciences
Accuracy of short-range missiles: CPT 10.17
Amount of rainfall for April: AEx 12.5, 12.10
Area and maximum depth of world lakes: 3.97
Atmospheric ammonium ions: 2.112
Atomic weight of silver: 8.40
Carbon monoxide readings in Rochester: Ex 8.13, Ex 9.5
Density of nitrogen: 2.188
Density of the earth: 2.118, 9.57
Duration and path width of solar eclipses: 3.28
Durations of eruptions of Old Faithful: 2.46
Effects of cloud seeding on rainfall amounts: 14.35
Elevations of towns in upstate New York: 2.96
Number of sit-ups in 1 minute: 10.36
Old Faithful eruption data: 3.102
Parallax of the sun: 9.32
Precipitation in New York State: 6.110
Prediction of next eruption of Old Faithful: AEx 8.1, 8.17
Pressure and total aluminum content for Horn blende
rims: 13.80
Roughness coefficient for quartz sand grains: 14.75
Target error of short-range rockets: 10.148
Test flow rates in dual bell rockets: 10.46
Velocity of light: 9.159, 12.34
Water content of snow: AEx 8.5, 8.43
Water pollution readings: 9.156
Weather forecasts: 4.13
AEx 5.10 African-American roles in cinema releases: 11.16 Ages of antitrust offenders: 9.22
Amount that requires consultation with spouse before spending: 8.38
Anxiety test scores: 10.139 Attitudes toward death: 10.44 Bikers and body art: 5.68 Destruction-of-property offenses among school-age boys and girls: CPT 10.16
Determining the “goodness” of a test question: 10.154 Driving while drowsy: 5.81
Drug addiction: 5.74 Earphone use on flights: 5.91 Effect of suburb position on school population: 12.30 Establishing the reliability of a test: 13.21 Fear of darkness: 11.41
Fear of dentist by age: 3.81 Fear of public speaking: 9.109 Hate crimes: Ex 2.2 Households with guns: 11.25 Ideal age: 3.5, 12.33 Ideal age to live forever: 5.12 Images of political candidates: 10.97 Job satisfaction: Ex 8.15, Ex 8.20 Job satisfaction of nurses in magnet and non-magnet hospitals: 11.19
Job satisfaction rankings by workers and boss: 14.56 Legalization of marijuana for medical purposes: 9.107 Lifetime learning activities: 5.114
Marriage proposals by women: 10.103 Memory test scores: 10.16, 10.150 Methods of disciplining children: 6.126 Personality characteristics of police academy applicants:
AEx 10.20, 10.124 Proportions of Catholic and non-Catholic families in pri- vate schools: CPT 10.22
Psychology experiment: 10.7 Reporting cheating on exam: 5.109 Self-image test scores of public-assistance recipients:
Ex 9.6 Sizes of communities reared in and residing in: 11.33 Teenagers’ views on contemporary issues: 14.1, 14.2, 14.89
Teen gambling: 9.74, 10.85 Television news preference and political affiliation: 3.7 Testing prospective employees: Ex 8.16
Test scores of clerk-typist applicants: 8.165 Volunteer work by children: 9.104 Worker opinions on biometric technology: 5.92 Worker-supervisor relationships: 11.35
Public Health and Safety
Ages of volunteer ambulance members in upstate New York: 8.161
AIDS knowledge test scores: 10.146 Air pollution rankings of U.S cities: 14.58 Arrests for drug law violations: 12.50 Bike helmet laws: 9.86
Distance to nearest fire department: 8.152
“Five-second rule” for food safety: 2.171 Hand washing in public restrooms: 4.99 Helmet use with wheeled sports: 1.77 Medically Needy Program in Oregon: 5.22 Number of engines owned by fire departments: 8.6 Number of reported crimes by district: 11.60 Opinions on police agency organization by residence:
Ex 4.24 Police officer exams: CPT 4.16 Population and violent crime rate: 13.37 Quality of service station restrooms: 11.34 Scores on Emergency Medical Services Certification Examination: 8.149
Seat belt usage: 9.89, 11.32 Seriousness weights in index of crime: AEx 13.7, 13.49 Speed limits—85 th percentile rule: AEx 2.15 Tobacco settlement and population: 13.82 Traffic ticket and accident probability: 4.100 Weapons in school: 11.42
Sports
Archery: 5.9 Attempted passes by NFL quarterbacks: 2.208 Baseball batting average: 5.71
Comparison of college football poll rankings: 14.87 Distance to centerfield fence in MLB stadiums: 2.116 Distribution of gold, silver, and bronze medals at Olympics: 13.76
Durability of golf balls: 12.51 Duration of MLB games: 6.113, 8.153, 8.167, 10.72 Earnings of Nationwide Tour professional golfers: 2.189 Football players’ sprint times on artificial turf and grass:
10.145 Football’s winning coaches: 4.14 Graduation rates of NCAA tournament teams: 2.113 High school basketball: 2.17
High school basketball injuries: 4.98, 11.64 Home runs in MLB: 1.76, 2.20
MLB won/loss percentages for away games by division: 12.29
Most holes played by golfers: 11.51 NBA coach records: 6.97 NBA players in Olympics: 13.38 NBA players” points scored and personal fouls commit- ted per game: 3.1, 3.48, 3.105
NBA playoffs: 5.83 NCAA basketball: 4.44 Number of golf tournaments played by professionals: 2.170
Number of wins and earned run averages in MLB: 3.73 Odds against making professional sports team: AEx 4.7 Olympic biathlon: 5.65
Performance of Olympic gold medal winners over time: 3.25
PGA top money leaders and world rankings: 3.76 PGA tournament scores: 2.37
Points earned by NASCAR drivers: 2.207 Points per game and All-Star appearances of NBA play- ers: 13.43
Points scored by NBA teams: 2.7 Points scored for and against NFL teams: 12.47, 13.11 Running times on cinder tracks and synthetic tracks: 14.73
“Size” measurements for MLB stadiums: 3.23 Soccer goals: 2.31
Sports championship series: 4.167 Steroid testing for athletes: 4.73, 4.116, 5.116 Stride rate and speed of serious runners: 3.68 Success rates for PGA players from various distances from the greens: 3.71
Super Bowl odds: 4.43
Surveys and Opinion Polls
Attitudes of men and women on managing stress: 10.155
Cluster sampling: 1.56 Election poll: 1.68, Ex 4.8, Ex 4.9, Ex 4.14, Ex 4.15,
Ex 4.20 Female president of United States: 6.98 Grid sampling: 1.49
Managers and professionals working late: 9.75 Margins of error in nationwide polls: AEx 9.9, 9.79 Opinions on budget proposal: Ex 4.11, Ex 4.12, Ex 4.19 Opinions on executive compensation: 10.99 Political election: 8.68, Ex 10.12 Poll on proposed legislation: Ex 11.4 Poll on recycling: CPT 11.18 Random sampling: 1.50, 1.51 Refusing job offer because of family considerations: 10.98
Research Randomizer: 14.52 Sample size for customer survey: 9.166 Sampling frame: 1.48, 1.57 Sampling methods: 1.41 Sampling student bodies at two schools: 7.26
“Sexiest job” poll: 6.127 Support for “get tough” policy in South America: 10.152 Systematic sample: 1.53
Telephone surveys: 1.52
Transportation
Ages of urban transit rail vehicles: AEx 7.3 Airline complaints: 2.14, 2.187, 3.77, 4.12, 11.62 Airline engine reliability: 5.110
Airline on-time rates: 2.73, 2.99, 2.115, 6.132, 14.62 Airport runways: 4.51
Automobile speeds on expressway: 6.58 Baggage weights of airline passengers: 7.60 Bicycle fatalities and injuries: 4.54 Bridge conditions in North Carolina: 5.120 Car rental rates: 10.45, 14.8
Death rates on rural roads: 13.24 Distance between interchanges on interstates: 2.61 Fuel economy of SUVs: 9.33
Mass transit system data for large cities: 3.100 Maximum speed limits on interstate highways: 3.6 Miles per gallon of gasoline: 3.87, Ex 8.18, 8.172, 9.140 Motor-fuel consumption: 2.78
Number of miles of interstate highways: 2.60, 2.192, 3.45, 3.47, 3.74
On-time commutes: 4.74 Railroad riders: 4.9 Railroad violations: 4.133 Ship arrivals in harbor: 5.35, 5.103 Space shuttle reliability: 4.114 Speed of Eurostar train: 8.36 Speeds of automobiles: 2.43 Stopping distance on wet surface: 2.185, Ex 3.2, 12.43 Structurally deficient bridges: 2.98, 2.125
Taxi fares: 8.5 Thunderstorms and on-time flights: 4.150 Traffic circles: 4.148
Traffic control: 4.30, 4.137 Traffic fatalities: 2.114, 4.4 Transportation in D.C.: 4.55 Travel time index: 9.186 Wait times in airport security lines: 5.24
Trang 5What does StatisticsNow’s integrated learning system do?
This dynamic program allows you to build a learning plan for yourself…based on what you know and what youneed to know to get a better grade in your course Icons within the text suggest opportune times to
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Trang 61pass™ gives you access to:
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Trang 7Robert Johnson Patricia Kuby
Monroe Community College
Elementary Statistics
T E N T H E D I T I O N
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Trang 9C H A P T E R 5 Probability Distributions (Discrete Variables) 268
C H A P T E R 6 Normal Probability Distributions 312
C H A P T E R 7 Sample Variability 360
C H A P T E R 8 Introduction to Statistical Inferences 394
C H A P T E R 9 Inferences Involving One Population 472
C H A P T E R 1 0 Inferences Involving Two Populations 544
C H A P T E R 1 1 Applications of Chi-Square 618
C H A P T E R 1 2 Analysis of Variance 656
C H A P T E R 1 3 Linear Correlation and Regression Analysis 694
C H A P T E R 1 4 Elements of Nonparametric Statistics 748
Trang 11Chapter 2 Descriptive Analysis and Presentation of Single-Variable Data 38
Chapter 3 Descriptive Analysis and Presentation of Bivariate Data 144
Trang 12Chapter 5 Probability Distributions (Discrete Variables) 268
Chapter 6 Normal Probability Distributions 312
Chapter 8 Introduction to Statistical Inferences 394
Chapter 9 Inferences Involving One Population 472
Chapter 10 Inferences Involving Two Populations 544
10.3 Inferences Concerning the Mean Difference Using Two
10.4 Inferences Concerning the Difference Between Means Using Two
Trang 1310.5 Inferences Concerning the Difference Between Proportions Using Two
10.6 Inferences Concerning the Ratio of Variances Using Two
Chapter 11 Applications of Chi-Square 618
Chapter 12 Analysis of Variance 656
Chapter 13 Linear Correlation and Regression Analysis 694
Chapter 14 Elements of Nonparametric Statistics 748
Introductory Concepts and Review Lessons with Answers 885
Trang 15Our Approach
Over the years, Elementary Statistics has developed into a readable introductory
textbook that promotes learning, understanding, and motivation by presentingstatistics in a real-world context for students without sacrificing mathematical
rigor In addition, Elementary Statistics has responded to the gradual acceptance by
almost every discipline that statistics is a most valuable tool for them As a sult, the applications, examples, projects, and exercises contain data from a widevariety of areas of interest, including the physical and social sciences, publicopinion and political science, business, economics, and medicine
re-Now, more than 30 years after Elementary Statistics was first published, at least
one statistics course is recommended for students in all disciplines, because tistics today is seen as reaching into multiple areas of daily life Despite thischange in perception, our approach has not changed We continue to strive forreadability and a common-sense tone that will appeal to students who are in-creasingly more interested in application than in theory
sta-Coverage in the New Edition
NEW Chapter 1—Statistics: This chapter has been rewritten to place a
greater emphasis on interpretation of statistical information when learning keystatistical terms and procedures
Chapter 3—Descriptive Analysis and Presentation of Bivariate Data:
for those who prefer this approach Continuing with relationships between twovariables makes for a logical progression of material and satisfies students’ nat-ural curiosity about two variables after studying descriptive statistics of one vari-able In addition, this early introduction allows instructors to go through nearlyall of the thought process for a hypothesis test without any of the technicalnames and procedures Later, in Chapter 8, when it comes time to introduce thehypothesis test procedure, by reusing the correlation decision as an introductoryexample, students will feel comfortable with the “new” testing process
NEW Chapter 4—Probability: This chapter has been completely revised
with increased focus on analysis as opposed to formulas to increase student terest and comprehension of this sometimes challenging topic
in-p-Value and classical approaches to hypothesis testingare introduced arately, but are thereafter presented side-by-side to offer pedagogical flexibilityand to emphasize their comparability
sep-Preface
ix
Trang 16Tour of the New Edition
Chapter Outlines
appear at the beginning of each chapter to
give an overview of what is to be presented
Gain a better understanding of algebraic
and basic statistical concepts with author
Patricia Kuby’s Introductory Concepts and
Review Lessons with Answers now included
with this text Explanations of topics are
presented so that one can learn the fine
details without getting lost in the statistical
involvement, and once the basic concepts
are mastered, the step to incorporating
them into statistics will be natural and
fluid Additional practice is provided to
ensure understanding
Throughout the chapter, this icon introduces a list of resources on the StatisticsNow website at
The National Center for Health Statistics (NCHS) provides statistical
informa-people Recent data from NCHS give the average height of females in the United States to be 63.7 inches, with a standard deviation of 2.75 inches.
8.1 Were They Shorter Back Then?
The average height for an early century English man was approximately 5' 6'' For 17th-century English women, it England remained virtually unchanged in
17th-WERE THEY SHORTER BACK THEN?
colonists grew taller Averages for modern about 5' 3 3/4'' for women The main rea- trition, notably increased consumption of meat and milk, and antibiotics.
Source: http://www.plimoth.org/Library/l-short.htm
C H A P T E R Introduction
to Statistical Inferences
8.1 Were They Shorter Back Then?
8.2 The Nature of Estimation
8.3 Estimation of Mean ( known)
8.4 The Nature of Hypothesis Testing
8.5 Hypothesis Test of Mean ( known): A Probability-Value
introduction,” demonstrating statistics
in action with respect to the specific
chapter’s material Each example
illustrates a familiar situation using
statistics in a relevant, approachable
manner for the student
Trang 17d On the same histogram used in part b of Exercise 8.1 on page 396:
(i) Draw a vertical line at the sized population mean value, 63.7 (ii) Draw a horizontal line segment showing the 95% confidence inter- val found in part b.
hypothe-e Does the mean 63.7 fall in the
in-terval? Explain what this means.
f Describe the relationship between the two lines drawn on your graph for part c
of Exercise 8.2 on page 396 and the two lines drawn for part d of this exercise.
g On the basis of the results obtained lier, does it appear that the females in this study, on average, are the same height as all females in the United States
ear-as reported by the NCHS? Explain.
Chapter Project
Were They Shorter Back Then?
Data from the National Center for Health Statistics indicate that the average height of a female in the United States is 63.7 inches with a standard devia- tion of 2.75 inches Use the data on heights of fe- males in the health profession from Section 8.1,
“Were They Shorter Back Then?” (p 395), to swer the following questions [EX08-001]
an-65.0 66.0 64.0 67.0 59.0 69.0 66.0 69.0 64.0 61.5 63.0 62.0 63.0 64.0 72.0 66.0 65.0 64.0 67.0 68.0 70.0 63.0 63.0 68.0 58.0 60.0 63.5 66.0 64.0 62.0 64.5 69.0 63.5 69.0 62.0 58.0 66.0 68.0 59.0 56.0 64.0 66.0 65.0 69.0 67.0 66.5 67.5 62.0 70.0 62.0
Putting Chapter 8 to Work
8.199a Are the assumptions of the confidence interval and hypothesis test methods of this chapter satisfied? Explain.
b Using the sample data and a 95% level
of confidence, estimate the mean height of females in the health profes- sion Use the given population standard deviation of 2.75 inches.
NEW and Updated
end of each chapter,
bring the Chapter
Opening Sections full
Find the area under the normal curve to the right of z 1.52: P(z 1.52).
S O L U T I O N The area to the right of the mean (all the shading in the figure) is ex- actly 0.5000 The problem asks for the shaded area that is not included in the 0.4357 Therefore, we subtract 0.4357 from 0.5000:
P(z 1.52) 0.5000 0.4357 0.0643 Note:As we have done here, always draw and label a sketch It is most helpful.
Make it a habit to write z with two decimal places and areas and
probabil-ities with four decimal places, as done in Table 3.
318 CHAPTER 6 Normal Probability Distributions
throughout the text,
present the step-by-step
solution process for
key statistical concepts
and methods
A P P L I E D
Remember going to kindergarten?
Maybe, maybe not! If you do member, your first concern was most likely whether you would have a good time and make some friends What would your teacher’s concerns have been?
re-Consider the information cluded in the graphic “Even in kindergarten, social skills trump.”
in-It describes the skills that garten teachers consider essential
kinder-or very impkinder-ortant Eight hundred kindergarten teachers (only a frac- tion of all of them) were surveyed, producing the skills and percent- ages reported Leading the list are
“Paying attention” and “Not being disruptive.” Of the 800 surveyed teachers,
Percentage of 800 kingergarten teachers surveyed who say these skills are essential or very important:
EVEN IN KINDERGARTEN, SOCIAL SKILLS TRUMP
Data from Julia Neyman and Alejandro Gonzalez, © 2004 USA Today.
Paying attention 86%
Not being 86%
Following directions 83%
Getting along with others 83%
solving 61%
Problem-Knowing the alphabet 32%
0%
100%
Counting
to 20 27%
Trang 18NEW Did You Know?
short history stories
and fun facts provide
The standard normal variable z is our test statistic for this hypothesis test.
Critical region: The set of values for the test statistic that will cause us to reject the null hypothesis The set of values that are not in the critical region is called the
noncritical region(sometimes called the acceptance region).
Recall that we are working under the assumption that the null hypothesis
is true Thus, we are assuming that the mean shearing strength of all rivets in the sampled population is 925 If this is the case, then when we select a ran-
dom sample of 50 rivets, we can expect this sample mean, x, to be part of a
normal distribution that is centered at 925 and to have a standard error of
mean values will be greater than 920.8 (a value 1.65 standard errors below the mean: 925 (1.65)(2.55) 920.8) Thus, if Hois true and 925, then we expect x to be greater than 920.8 approximately 95% of the time and less than
920.8 only 5% of the time.
If, however, the value of x that we obtain from our sample is less than
920.8—say, 919.5—we will have to make a choice It could be that either: (A)
such an x value (919.5) is a member of the sampling distribution with mean
925 although it has a very low probability of occurrence (less than 0.05), or (B)
x 919.5 is a member of a sampling distribution whose mean is less than 925,
which would make it a value that is more likely to occur.
DID YOU KNOW
Disputes in Approach
Statistics is not just matics There are different ways to approach statistical in- ferences and different ways to interpret what the data are telling The more significant the differences, the more likely there are to be heated dis- agreements between those of opposing viewpoints Just such
mathe-a dispute erupted in 1935 mathe-at mathe-a Royal Statistical Society dis- cussion when R A Fisher challenged Jerzy Neyman with regard to his being fully ac- quainted with the topic being discussed The dispute cen- tered on Pearson and Neyman’s use of confidence intervals and approach to hy- pothesis testing versus Fisher’s intervals and concept of p- values in significance testing.
The feud lasted until Fisher’s death in 1962.
Any distribution with 925
NEW and Updated
With nearly 550 new
exercises and almost
NEW and Updated
More than 300 classic
available on the
Student’s Suite CD-ROM,
as well as the solutions to
odd-numbered exercises
With more than 2100
have ample opportunity
for practice and
instruc-tors will have a greater
choice of exercises to
use in their course
S E C T I O N 8 3 E X E R C I S E S
8.19 Discuss the conditions that must exist before
we can estimate the population mean using the terval techniques of formula (8.1).
in-8.20 Determine the value of the confidence
coeffi-cient z(/2) for each situation described:
a 1 0.90 b 1 0.95
8.21 Determine the value of the confidence
coeffi-cient z(/2)for each situation described:
a 98% confidence b 99% confidence
8.23 Given the information, the sampled
popula-tion is normally distributed, n 16, x 28.7, and
6:
a Find the 0.95 confidence interval for .
b Are the assumptions satisfied? Explain
8.24 Given the information, the sampled
popula-tion is normally distributed, n 55, x 78.2, and
12:
a Find the 0.98 confidence interval for .
b Are the assumptions satisfied? Explain
8.25 Given the information, n 86, x 128.5,
a Find the 0.90 confidence interval for .
b Are the assumptions satisfied? Explain
8.26 Given the information, n 22, x 72.3, and
6 4:
Skillbuilder Applet Exercisesmust be worked using an accompanying applet found on your Student’s Suite CD-ROM or at
the StatisticsNow website at http://1pass.thomson.com.
Datasetscan be found on your Student’s Suite CD-ROM or at the
StatisticsNow website at http://1pass.thomson.com.
Chapter Exercises
6.101According to Chebyshev’s theorem, at least how much area is there under the standard normal
distribution between z 2 and z 2? What is
the actual area under the standard normal
distri-bution between z 2 and z 2?
6.102The middle 60% of a normally distributed population lies between what two standard scores?
6.103Find the standard score (z) such that the area above the mean and below z under the nor-
mal curve is:
Go to the StatisticsNow website http://1pass.thomson.com to
• Assess your understanding of this chapter
• Check your readiness for an exam by taking the Pre-Test quiz and exploring the resources in the Personalized Learning Plan
Datasetscan be found on your Student’s Suite CD-ROM or at the
StatisticsNow website at http://1pass.thomson.com.
Trang 19New and Updated Expanded Chapter Review, tailored to reviewers’ feedback
and students’ needs, functions as a chapter study guide at the end of each ter Each Chapter Review includes:
out the relationships between previously covered material
S E C T I O N 6 4 E X E R C I S E S
6.39 Skillbuilder Applet Exercisedemonstrates that probability is equal to the area under a curve Given that college students sleep
an average of 7 hours per night with a standard de- viation equal to 1.7 hours, use the scroll bar in the applet to find the following:
a P(a student sleeps between 5 and 9 hours)
b P(a student sleeps less than 4 hours)
6.41 Given x 58, 43, and 5.2, find z.
6.42 Given x 237, 220, and 12.3, find z.
6.43 Given that x is a normally distributed random
variable with a mean of 60 and a standard tion of 10, find the following probabilities:
devia-a. P (x 60) b. P (60 x 72) c P (57 x 83)
d. P (65 x 82) e P (38 x 78) f P (x 38)
6.44 Given that x is a normally distributed random
variable with a mean of 28 and a standard tion of 7, find the following probabilities:
devia-a. P (x 28) b. P (28 x 38) c P (24 x 40)
d. P (30 x 45) e P (19 x 35) f P (x 48)
6.45 Using the information given in Example 6.10
(p 324):
a Find the probability that a randomly selected
Skillbuilder Applet Exercisesmust be worked using an accompanying applet found on your Student’s Suite CD-ROM or at
the StatisticsNow website at http://1pass.thomson.com.
Datasetscan be found on your Student’s Suite CD-ROM or at the
StatisticsNow website at http://1pass.thomson.com.
Updated Skillbuilder
in Section and Chapter
Exercises, help students
“see” statistical concepts
and allow hands-on
exploration of statistical
concepts and calculations
To explore the
accompanying applets,
students can find them
on the Student’s Suite
prob-ety of variables that have this normal distribution
or are reasonably well approximated by it.
In the next chapter we will examine sampling distributions and learn how to use the standard normal probability to solve additional applications.
Vocabulary and Key Concepts
area representation for bility (p 316)
proba-bell-shaped curve (p 315) binomial distribution (p 343) binomial probability (p 343) continuity correction factor ( 344)
continuous random variable (pp 315, 344) discrete random variable (pp 315, 344) normal approximation of bino- mial (p 343)
l ( 316)
percentage (p 316) probability (p 316) proportion (p 316) random variable (p 315) standard normal distribution (pp 316, 323, 338)
t d d ( 316 323)
much of the material they truly understand
have been learned through the course of the chapter accompanied by sponding review exercises and section references to ensure comprehension
corre-of the chapter material
Trang 20• Chapter Exercises, which offer practice on all the concepts found in thechapter while also tying in comprehensive material learned from previouschapters.
Chapter Exercises
6.101According to Chebyshev’s theorem, at least how much area is there under the standard normal
distribution between z 2 and z 2? What is
the actual area under the standard normal
distri-bution between z 2 and z 2?
6.102The middle 60% of a normally distributed population lies between what two standard scores?
6.103Find the standard score (z) such that the area above the mean and below z under the nor-
mal curve is:
Go to the StatisticsNow website http://1pass.thomson.com to
• Assess your understanding of this chapter
• Check your readiness for an exam by taking the Pre-Test quiz and exploring the resources in the Personalized Learning Plan
Datasetscan be found on your Student’s Suite CD-ROM or at the
StatisticsNow website at http://1pass.thomson.com.
k What percentage of the SAT scores are below 450?
l What percentage of the SAT scores are above 575?
m What SAT score is at the 95th percentile? plain what this means.
Ex-Chapter Project
Intelligence Scores
All normal probability distributions have the same shape and distribution relative to the mean and standard deviation In this chapter we learned how
to use the standard normal probability distribution
to answer questions about all normal distributions.
Let’s return to distribution of IQ scores discussed in the Section 6.1, “Intelligence Scores” (p 313), and try out some of our new knowledge.
e What IQ score is at the 95th percentile? plain what this means.
Ex-Chapter Practice Test
PART I: Knowing the Definitions
Answer “True” if the statement is always true If the statement is not always true, replace the words shown in bold with words that make the statement always true.
6.1 The normal probability distribution is
sym-metric about zero.
6.2 The total area under the curve of any normal
distribution is 1.0.
6.3 The theoretical probability that a particular
value of a continuous random variable will
occur is exactly zero.
6.4 The unit of measure for the standard score is
the same as the unit of measure of the
independent events.
6.10 The most common distribution of a
continu-ous random variable is the binomial
proba-bility.
PART II: Applying the Concepts
6.11 Find the following probabilities for z, the
standard normal score:
figure at the bottom of the page.
6.14 The lifetimes of flashlight batteries are mally distributed about a mean of 35.6 hr with a standard deviation of 5.4 hr Kevin se- lected one of these batteries at random and tested it What is the probability that this one battery will last less than 40.0 hr?
nor-6.15 The lengths of time, x, spent commuting
daily, one-way, to college by students are lieved to have a mean of 22 min with a stan-
Chap-ter Opening Sections to answer the questions proposed at the beginning ofthe chapter, using the knowledge gained from studying the chapter
mas-tery of the material before being tested in class Correct responses are in theback of the textbook
Trang 21NEW and Updated MINITAB, Excel, and TI-83/84 instructions are duced in the text alongside appropriate material This approach allows instruc-tors to choose which statistical technology, if any, they would like to incorporateinto their course
intro-NEW and Updated With more than 400 data sets, ranging from small tolarge, students have the opportunity to practice using their statistical calculator
or computer
technologies Found on the Student’s Suite CD-ROM, as well as in
Community College
Community College
Note:These technology manuals are available in both print and electronic mats Instructors, contact your sales representative to find out how these man-uals can be custom published for your course
for-TE C H N O LO GY I N STR U CTI O N S: C O R R E L ATI O N C O E F F I C I E NT
Input the x-variable data into C1 and the corresponding y-variable data into
C2; then continue with:
Choose: Stat Basic Statistics Correlation .
Enter: Variables: C1 C2 OK
Input the x-variable data into column A and the corresponding y-variable
data into column B, activate a cell for the answer; then continue with:
Choose: Insert function, f x Statistical CORREL OK
Enter: Array 1: x data range
Array 2: y data range OK
Input the x-variable data into L1 and the corresponding y-variable data into
L2; then continue with:
Choose: 2nd CATALOG DiagnosticOn* ENTER ENTER
Choose: STAT CALC 8:LinReg(a bx)
Enter: L1, L2
*DiagnosticOn must be selected for r and r 2 to show Once set, omit this step.
Understanding the Linear Correlation Coefficient
The following method will create (1) a visual meaning for correlation, (2) a sual meaning for what the linear coefficient is measuring, and (3) an estimate
vi-for r The method is quick and generally yields a reasonable estimate when the
“window of data” is approximately square.
Note:This estimation technique does not replace the calculation of r It is very
sensitive to the “spread” of the diagram However, if the “window of data” is approximately square, this approximation will be useful as a mental estimate
busi-On Airplane Hotel Room All Other
a Express the table as percentages of the total
b Express the table as percentages of the row tals Why might one prefer the table to be ex- pressed this way?
to-c Express the table as percentages of the column totals Why might one prefer the table to be ex- pressed this way?
3 4 Th “O tl k f b i t l ” hi
Datasetscan be found on your Student’s Suite CD-ROM or at the
StatisticsNow website at http://1pass.thomson.com.
Trang 22Working with Your Own
at the end of each of the
four major parts of the
book, are designed to
encourage further
exploration, independent
student learning, and
critical thinking These
can be used as individual
class projects or in small
groups
Working WithYour Own Data 393
10 Construct a frequency distribution of the 50 sample means found in questions 8 and 9.
11 Construct a histogram of the frequency tribution of observed sample means.
dis-12 Calculate the mean x and standard tion s xof the frequency distribution formed
devia-by the 50 sample means.
13 Compare the observed values of x and s x
with the values of xand xDo they agree?
Does the empirical distribution of x look
like the theoretical one?
Here are 100 random samples of size 3 that were generated by computer:
392 CHAPTER 7 Sample Variability
Putting Probability to Work
The sampling distribution of sample means and the central limit theorem are very important to the de- velopment of the rest of this course The proof, which requires the use of calculus, is not included
in this textbook However, the truth of the SDSM and the CLT can be demonstrated both theoreti- cally and by experimentation The following activ- ities will help to verify both statements.
b Draw a histogram of this probability tribution.
dis-c Calculate the mean, , and the standard
deviation,, for this population.
B THE SAMPLING DISTRIBUTION, THEORETICALLY
Let’s study the theoretical sampling distribution formed by the means of all possible samples of size
3 that can be drawn from the given population.
2 Construct a list showing all the possible ples of size 3 that could be drawn from this population (There are 27 possibilities.)
sam-3 Find the mean for each of the 27 possible samples listed in answer to question 2.
4 Construct the probability distribution (the theoretical sampling distribution of sample means) for these 27 sample means.
5 Construct a histogram for this sampling tribution of sample means.
dis-6 Calculate the mean xand the standard ror of the mean xusing the probability distribution found in question 4.
er-7 Show that the results found in questions 1c, 5, and 6 support the three claims made
by the sampling distribution of sample means and the central limit theorem Cite specific values to support your conclusions.
C THE SAMPLING DISTRIBUTION, EMPIRICALLY
Let’s now see whether the sampling distribution of sample means and the central limit theorem can be verified empirically; that is, does it hold when the sampling distribution is formed by the sample means that result from several random samples?
8 Draw a random sample of size 3 from the given population List your sample of three numbers and calculate the mean for this sample.
You may use a computer to generate your ples You may take three identical “tags” numbered
sam-0, 3, and 6, put them in a “hat,” and draw your sample using replacement between each drawing.
Or you may use dice; let 0 be represented by 1 and 2; 3, by 3 and 4; and 6, by 5 and 6 You may also use random numbers to simulate the drawing of your samples Or you may draw your sample from the list of random samples at the end of this sec- tion Describe the method you decide to use (Ask your instructor for guidance.)
9 Repeat question 8 forty-nine more times so that you have a total of 50 sample means that have resulted from samples of size 3.
Working with Your Own Data
Trang 23Learning Resources
that helps students gauge their unique study needs and makes the most of theirstudy time by building focused, chapter-by-chapter, Personalized Learning Plansthat reinforce key concepts
give you an initial assessment of your knowledge
questions, outline key elements for review
assess students’ mastery of core chapter concepts; results can be e-mailed tothe instructor!
Note: StatisticsNow also serves as a one-stop portal for nearly all your
Ele-mentary Statistics resources, which are also found on the Student’s Suite
CD-ROM, as well as the Interactive Video Skillbuilder CD-ROM Throughoutthe text, StatisticsNow icons have been thoughtfully placed to direct students
to the resources they need when they need them Access StatisticsNow via
Trang 24Learning Resources (continued)
Student’s Suite CD-ROM
(0-495-10533-3) This valuable learning resource includes:
M Myers, Harrisburg Community College
• Updated Excel Manualby Diane L Benner and Linda M Myers, Harrisburg Area Community College
• Updated TI-83/84 Manualby Kevin Fox, Shasta College
• NEW and Updated Skillbuilder Appletsto accompany dicated exercises from the text
in-• NEW and Updated Classic Exercisesfor each chapter of the text
con-cepts presented in the early chapters of your text
Statistical procedures
Internet Companion for Statistics, InfoTrac® College Edition, and muchmore
hours of helpful, interactive video instruction Students can watch as an instructor walks them through key examples from the text, step by step—giving a foundation
in the skills that they need to know Each example found
on the CD-ROM is identified by icons located in the margin
of the text Think of it as portable office hours!
their own computer microphones) to tutors
who will skillfully guide them through a
problem using an interactive whiteboard
for illustration Up to 40 hours of live
tutoring a week is available with every
new book and can be accessed through
Trang 25The Book Companion Website offers book- and course-specific resources, such
as tutorial quizzes for each chapter and data sets for exercises Students can
Updated Student Solutions Manual (0-495-10531-7), written by PatriciaKuby, includes fully worked out solutions for all odd-numbered exercises andalso provides hints, tips, and additional interpretation for specific exercises
University, offers practical information on how to use the Internet to increasestudents’ understanding of statistics Organized by key topics covered in the in-troductory course, the text offers a brief review of a topic, listings of appropriatewebsites, and study questions designed to build students’ analytical skills This
Trang 26Student Access Information
To summarize, many of the items mentioned thus far are available either on
stu-dents did not purchase this book new or if they purchased a Basic Select text—containing no media resources—but would like to use any of the resources men-
study tools The following chart summarizes this access information
Student’s Suite Interactive Video
iLrn Statistics XStatisticsNow X
College EditionMichael Larsen’s XInternet Companion for Statistics
MINITAB Manual X (Found in StatisticsNow) XExcel Manual X (Found in StatisticsNow) XTI-83/84 Graphing X (Found in StatisticsNow) XCalculator Manual
Data sets X (Found in StatisticsNow) X
Excel Add-inSkillbuilder Applets X (Found in StatisticsNow) X
Trang 27Instructor Resources
Suite CD-ROM, in addition to:
complete solutions
contain-ing all of the figures from the
.jpg files
answer, and applied and computational questions by section, authored by Mohammed A El-Saidi of Ferris State University
JoinIn content for electronic response systems, written by BryanJames and Joanna Pruden of Pennsylvania College of Technol-ogy Instructors can transform their classroom and assess stu-dents’ progress with instant in-class quizzes and polls TurningPoint software lets you pose book-specific questions and displaystudents’ answers seamlessly within Microsoft PowerPoint lec-ture slides, in conjunction with a choice of “clicker” hardware.Enhance how your students interact with you, your lecture, and each other
for your introductory statistics course It motes learning through interaction on theweb and can be used as the sole text for acourse or in conjunction with a traditionaltext Students internalize the behavior of sta-tistical concepts by interacting with hundreds
pro-of applets (simulations and calculations) andreceiving immediate feedback on practiceitems Effective for both distance and on-campus courses, CyberStats provides a learn-ing opportunity that cannot be delivered inprint Instructors interested in using this fortheir course should contact their local salesrepresentative CyberStats is available for
Trang 28Updated iLrn Statisticsis your system for homework, integrated testing, andcourse management on the web! Using iLrn, instructors can easily set up onlinecourses; assign tests, quizzes, and homework; and monitor students’ progress,enabling them to mentor students on the right points at the right time Studentresponses are automatically graded and entered into the iLrn grade book, mak-ing it easy for you to assign and collect homework or offer testing over the web.
parts:
used for testing, homework, or quizzing You choose! Contact your salesrepresentative to find out how get access to this valuable resource
classroom management and assesses students on homework, quizzes, or ams, in the process of doing real data analysis on the web
Trang 29It is a pleasure to acknowledge the aid and encouragement we have received throughout the development of this text from students and colleagues at Monroe Community College In addition, special thanks to all the reviewers who read and offered suggestions about this and previous editions:
Nancy Adcox, Mt San Antonio College
Paul Alper, College of St Thomas
William D Bandes, San Diego Mesa College
Matrese Benkofske, Missouri Western State College
Tim Biehler, Fingerlakes Community College
Barbara Jean Blass, Oakland Community College
Austin Bonis, Rochester Institute of Technology
Nancy C Bowers, Pennsylvania College of Technology
Shane Brewer, College of Eastern Utah, San Juan Campus
Robert Buck, Slippery Rock University
Louis F Bush, San Diego City College
Ronnie Catipon, Franklin University
Rodney E Chase, Oakland Community College
Pinyuen Chen, Syracuse University
Wayne Clark, Parkland College
David M Crystal, Rochester Institute of Technology
Joyce Curry and Frank C Denny, Chabot College
Larry Dorn, Fresno Community College
Shirley Dowdy, West Virginia University
Thomas English, Pennsylvania State University, Erie
Kenneth Fairbanks, Murray State University
Dr William P Fox, Francis Marion University
Joan Garfield, University of Minnesota General College
Monica Geist, Front Range Community College
David Gurney, Southeastern Louisiana University
Edwin Hackleman
Carol Hall, New Mexico State University
Silas Halperin, Syracuse University
Noal Harbertson, California State University, Fresno
Hank Harmeling, North Shore Community College
Bryan A Haworth, California State College at Bakersfield
Harold Hayford, Pennsylvania State University, Altoona
Jim Helms, Waycross College
Marty Hodges, Colorado Technical University
John C Holahan, Xerox Corporation
James E Holstein, University of Missouri
Soon B Hong, Grand Valley State University
Robert Hoyt, Southwestern Montana University
Peter Intarapanach, Southern Connecticut State University
T Henry Jablonski, Jr., East Tennessee State University
Brian Jean, Bakersfield University
Jann-Huei Jinn, Grand Valley State University
Sherry Johnson
Meyer M Kaplan, The William Patterson College of New
Jersey
Michael Karelius, American River College
Anand S Katiyar, McNeese State University
Jane Keller, Metropolitan Community College
Gayle S Kent, Florida Southern College
Andrew Kim, Westfield State College
Amy Kimchuk, University of the Sciences in Philadelphia
Raymond Knodel, Bemidji State University Larry Lesser, University of Northern Colorado Natalie Lochner, Rollins College
Robert O Maier, El Camino College Linda McCarley, Bevill State Community College Mark Anthony McComb, Mississippi College Carolyn Meitler, Concordia University Wisconsin John Meyer, Muhlenberg College
Jeffrey Mock, Diablo Valley College David Naccarato, University of New Haven Harold Nemer, Riverside Community College John Noonan, Mount Vernon Nazarene University Dennis O’Brien, University of Wisconsin, LaCrosse Chandler Pike, University of Georgia
Daniel Powers, University of Texas, Austin Janet M Rich, Miami-Dade Junior College Larry J Ringer, Texas A & M University John T Ritschdorff, Marist College John Rogers, California Polytechnic Institute at San Luis Obispo
Neil Rogness, Grand Valley State University Thomas Rotolo, University of Arizona Barbara F Ryan and Thomas A Ryan, Pennsylvania State University
Robert J Salhany, Rhode Island College Melody Smith, Dyersburg State Community College
Dr Sherman Sowby, California State University, Fresno Roger Spalding, Monroe County Community College Timothy Stebbins, Kalamazoo Valley Community College Howard Stratton, State University of New York at Albany Larry Stephens, University of Nebraska-Omaha
Paul Stephenson, Grand Valley State University Richard Stockbridge, University of Wisconsin, Milwaukee Thomas Sturm, College of St Thomas
Edward A Sylvestre, Eastman Kodak Co.
Gwen Terwilliger
William K Tomhave, Concordia College, Moorhead, MN Bruce Trumbo, California State University, Hayward Richard Uschold, Canisius College
John C Van Druff, Fort Steilacoom Community College Philip A Van Veidhuizen, University of Alaska John Vincenzi, Saddleback College
Kenneth D Wantling, Montgomery College Joan Weiss, Fairfield University
Mary Wheeler, Monroe Community College Barbara Whitney, Big Bend Community College Sharon Whitton, Hofstra University
Don Williams, Austin College Rebecca Wong, West Valley College Pablo Zafra, Kean University Yvonne Zubovic, Indiana University Purdue University, Fort Wayne
Robert Johnson Patricia Kuby
Trang 301.5 Comparison of Probability and Statistics
1.6 Statistics and Technology
1
Trang 31The U.S Census Bureau annually publishes the Statistical Abstract of the United
States, a 1000-page book that provides us with a statistical insight into many
of the most obscure and unusual facets of our lives This is only one of sands of sources for all kinds of things you have always wanted to know aboutand never thought to ask about Are you interested in how many hours wework and play? How much we spend on snack foods? How the price of RedDelicious apples has gone up? All this and more—much more—can be found
thou-in the Statistical Abstract (http://www.census.gov/statab/www).
The statistical tidbits that follow come from a variety of sources and sent only a tiny sampling of what can be learned about Americans statistically.Take a look
repre-1
Throughout the chapter, this icon
introduces a list of resources on the
StatisticsNow website at
http://1pass.thomson.com
that will:
• Help you evaluate your
knowledge of the material
• Allow you to take an
exam-prep quiz
• Provide a Personalized Learning
Plan targeting resources that
address areas you should study
E-mail 32%
0%
50%
Telephone 24%
Workers say they would rather be contacted by companies they do business
with via e-mail than any other way
Direct mail 18%
Personal letter 17%
COMMUNICATION METHOD PREFERRED BY WORKERS
Data from Anne R Carey and Ron Coddington, © 2004 USA Today.
Source: Opinion research for Neenah paper
No 59%
Yes 23%
Nearly 6 in 10 Americans want the penny to remain in circulation
Not sure 18%
SHOULD THE PENNY BE ELIMINATED?
Data from Shannon Reilly and Chad Palmer, © 2004 USA Today.
Source: Harris Interactive
Data from USA Today, 10/13/2003.
Source: Alliance for Aging Research
Yes 63%
No 32% Don’t know 5%
WOULD YOU LIKE TO SEE YOUR 100TH BIRTHDAY?
Trang 32The preceding examples and thousands of other measures are used to describelife in the United States.
Consider the graphic “Would you like to see your 100th birthday?” If you hadbeen asked, “Do you want to live to be 100?” how would you have answered? Doyou believe the diagram accurately depicts your answer? Does it make you stopand wonder how the information was obtained and where it came from? Do youbelieve the “printed” material? As you work through Chapter 1, you will begin tolearn how to read and analyze statistical measures to arrive at appropriate conclu-sions Then you will be able to further investigate “Americans, Here’s Looking atYou” in the Chapter Project section with Exercises 1.88 and 1.89 (p 35)
DRIVING IS LEADING DANGER TO TEENS
Data from USA Today, © 2003.
Source: Insurance Institute for Highway Safety
About 3500 teenagers died in teen-driven vehicles in the United States in 2003—a death toll that tops that of any disease or injury for teens
16-year-old drivers have highest fatal crash rate
16
17 18 19 20–24 25–29 30–59 60–69 70+
Driver age Fatal crash involvement per 100 million miles traveled 9.3
8.3 6.5 7.2 4.3 2.3 1.6 1.6 4.1
S E C T I O N 1 1 E X E R C I S E S
this section seem to suggest that
informa-tion is about what populainforma-tion? Is that the
col-lected and used to determine the statistics
reported in “Communication method
pre-ferred by workers.”
re-ported in the graphic “Would you like to
see your 100th birthday?” Describe what
that statistic tells you
d Consider the graphic “Should the penny beeliminated?” If you had been asked, howwould you have responded? Do you believeyour answer is represented accurately in thediagram? What does the percentage associatedwith your answer really mean? Explain
e How do you interpret the 7.2 that is listed fordriver age of 19 in the graphic “Driving is lead-ing danger to teens”?
what the word statistics means to you right
now
the word random means to you right now.
what the word sample means to you right
now
StatisticsNow website at http://1pass.thomson.com.
communication method worker preferred
63% of those people surveyed
7.2 fatal crash per 100 millions miles traveled for 19-year-olds
Trang 33As we embark on our journey into the study of statistics, we must begin with
the definition of statistics and expand on the details involved.
Statistics has become the universal language of the sciences As potentialusers of statistics, we need to master both the “science” and the “art” of usingstatistical methodology correctly Careful use of statistical methods will enable
us to obtain accurate information from data These methods include (1) fully defining the situation, (2) gathering data, (3) accurately summarizing thedata, and (4) deriving and communicating meaningful conclusions
care-Statistics involves information, numbers and visual graphics to summarize
this information, and their interpretation The word statistics has different
mean-ings to people of varied backgrounds and interests To some people it is a field of
“hocus-pocus” in which a person attempts to overwhelm others with incorrectinformation and conclusions To others it is a way of collecting and displaying in-
money? Java professionals think they do, reporting
long working hours at their jobs Java developers
from around the world were surveyed about the
number of hours they work weekly Listed here are
the average number of hours worked weekly in
various regions of the United States and the world
Source: Jupitermedia Corporation
a How many hours do you work per week (or
anticipate working after you graduate)?
b What happened to the 40-hour workweek?
Does it appear to exist for the Java
profes-sional?
ca-reer of being a Java professional seem
attrac-tive?
1.4 “What You Make Depends on Where You
Work.” When grouped by the type of organization
they work for, the risk takers (self-employed) rise
to the top again For Java developers, the employed make the most money, followed bythose at publicly held companies; both groups earnalmost twice as much as those who work for edu-cational institutions
self-a Examine the graph and describe carefully the
“picture” the graph has painted
b Does this graph make a career of being a employed Java professional seem attractive?
avail-ability of jobs in these six groupings of theworkplace?
d Can you conclude anything about the number
of hours a Java professional works each week
to earn these incomes?
Text not available due to copyright restrictions
Trang 34formation And to still another group it is a way of “making decisions in the face
of uncertainty.” In the proper perspective, each of these points of view is correct.The field of statistics can be roughly subdivided into two areas: descriptive
statistics and inferential statistics Descriptive statistics is what most people think
of when they hear the word statistics It includes the collection, presentation, and description of sample data The term inferential statistics refers to the tech-
nique of interpreting the values resulting from the descriptive techniques andmaking decisions and drawing conclusions about the population
Statistics is more than just numbers: it is data, what is done to data, what
is learned from the data, and the resulting conclusions Let’s use the followingdefinition:
Statistics:The science of collecting, describing, and interpreting data
Before going any further, let’s look at a few illustrations of how and when tistics can be applied
sta-A P P L I E D
E X A M P L E 1 1 Telling Us about Our Early Behavior
Remember going to kindergarten?
Maybe, maybe not! If you do member, your first concern wasmost likely whether you wouldhave a good time and make somefriends What would your teacher’sconcerns have been?
re-Consider the information cluded in the graphic “Even inkindergarten, social skills trump.”
in-It describes the skills that garten teachers consider essential
kinder-or very impkinder-ortant Eight hundredkindergarten teachers (only a frac-tion of all of them) were surveyed,producing the skills and percent-ages reported Leading the list are
“Paying attention” and “Not being disruptive.” Of the 800 surveyed teachers,86% considered these skills essential or very important Looking at all the per-centages, it is noted that they add up to more than 100% Apparently, theteachers surveyed were allowed to give more than one skill as an answer
The spa industry is booming The International SPA Association reports tics demonstrating that pampering people can certainly produce a profit In-come from spa/salons has increased by 409% over the 1997–2003 years In
statis-Percentage of 800 kingergarten teachers surveyed who say these skills are essential or very important:
EVEN IN KINDERGARTEN, SOCIAL SKILLS TRUMP
Data from Julia Neyman and Alejandro Gonzalez, © 2004 USA Today.
Paying attention 86%
Not being disruptive 86%
Following directions 83%
Getting along with others 83%
solving 61%
Problem-Knowing the alphabet 32% 0%
100%
Counting
to 20 27%
A P P L I E D
E X A M P L E 1 2 Describing Our Softer Side
Trang 35fact, the spa industry has become the fourth largest leisure industry in theUnited States It surpasses amusement/theme parks and movie theaters.
Much information is given in these graphs about the spa industry Considerwhat information would have to be collected to formulate the charts andgraphs—not just the number of spas but the type or category of spa as well asthe gender of those visiting a spa But where did these figures come from? Al-ways note the source to published statistics In this case the source is the In-ternational SPA Association The association is recognized worldwide as a pro-fessional organization and the voice of the spa industry
Newspapers publish graphs and chartstelling us how various organizations orpeoples think as a whole Do you everwonder how much of what we think isdirectly influenced by the information weread in these articles?
The following graphic reports that65% of companies do not worry that anincreasingly obese workforce will have
an impact on revenue or productivity
Where did this information come from?
Note the source, Duffey tions How did they collect the informa-tion? They conducted a survey of 450business and political figures A margin
Communica-of error is given at 5 percentage points (Remember to check the smallprint, usually at the bottom of a statistical graph or chart.) Based on this in-formation, between 60% and 70% of companies do not worry that an in-creasingly obese workforce will have an impact on revenue or productivity
A P P L I E D
E X A M P L E 1 3 Telling Us What Companies Think
Yes 27%
No 65%
Unsure 8%
Will an increasingly obese workforce have an impact
on companies’ revenue or productivity?
ARE COMPANIES CONCERNED ABOUT WORKERS’ WEIGHT?
Data from Darryl Haralson and Alejandro Gonzalez, © 2004 USA Today.
Margin of Error ±5 percentage points.
From Rochester Democrat and Chronicle, 12/5/2004 Reprinted with permission
Trang 36This seems rather amazing given the amount of information that appears inthe news about obesity and its effect on health, as well as the amount ofmoney and attention spent on diets and losing weight.
“One ounce of statistics technique requires one pound of common sense forproper application.”
Consider the International Shark Attack File (ISAF) The ISAF,
admin-istered by the American Elasmobranch Society and the Florida Museum ofNatural History, is a compilation of all known shark attacks It is shown in thegraph and chart that follow
A P P L I E D
E X A M P L E 1 4 Statistics Is Tricky Business
Image not available due to copyright restrictions
Trang 37sense—remember? Is the graph a bit misleading? What else could be ing the statistics shown here? First, one must consider how much of a coun-try’s or continent’s border comes in contact with an ocean Second, who istracking these attacks? In this case, it is stated at the top of the chart—TheFlorida Museum of Natural History, a museum in the United States Appar-ently, the United States is trying to keep track of unprovoked shark attacks.What else is different about the United States compared with the other areas?
influenc-Is the ocean a recreational area in the other places? What is the economy ofthese other areas, and/or who is keeping track of their shark attacks?
Remember to consider the source when reading a statistical report Be sureyou are looking at the complete picture
The uses of statistics are unlimited It is much harder to name a field in whichstatistics is not used than it is to name one in which statistics plays an integralpart The following are a few examples of how and where statistics are used:
re-sults
analyzed
In fact, the U.S government is probably the world’s greatest collector ofstatistical data
A very important part of the statistical process is that of studying the tical results and formulating appropriate conclusions These conclusions mustthen be communicated accurately—nothing is gained from research unless thefindings are shared with others Statistics are being reported everywhere:newspapers, magazines, radio, and television We read and hear about all kinds
statis-of new research results, especially in the health-related fields
To further continue our study of statistics, we need to “talk the talk.”
Sta-tistics has its own jargon, terms beyond descriptive staSta-tistics and inferential
statis-tics, that need to be defined and illustrated The concept of a population is the
most fundamental idea in statistics
Population: A collection, or set, of individuals, objects, or events whose ties are to be analyzed
proper-The population is the complete collection of individuals or objects that are
of interest to the sample collector The population of concern must be carefullydefined and is considered fully defined only when its membership list of ele-ments is specified The set of “all students who have ever attended a U.S col-lege” is an example of a well-defined population
Typically, we think of a population as a collection of people However, instatistics the population could be a collection of animals, manufactured objects,whatever For example, the set of all redwood trees in California could be apopulation
There are two kinds of populations: finite and infinite When the ship of a population can be (or could be) physically listed, the population is said
Trang 38member-to be finite When the membership is unlimited, the population is infinite The
books in your college library form a finite population; the OPAC (Online PublicAccess Catalog, the computerized card catalog) lists the exact membership Allthe registered voters in the United States form a very large finite population; ifnecessary, a composite of all voter lists from all voting precincts across the UnitedStates could be compiled On the other hand, the population of all people whomight use aspirin and the population of all 40-watt light bulbs to be produced bySylvania are infinite Large populations are difficult to study; therefore, it is cus-
tomary to select a sample and study the data in the sample.
Sample:A subset of a population
A sample consists of the individuals, objects, or measurements selectedfrom the population by the sample collector
Variable (or response variable): A characteristic of interest about each ual element of a population or sample
individ-A student’s age at entrance into college, the color of the student’s hair, thestudent’s height, and the student’s weight are four variables
Data value: The value of the variable associated with one element of a population
or sample This value may be a number, a word, or a symbol
For example, Bill Jones entered college at age “23,” his hair is “brown,” he
is “71 inches” tall, and he weighs “183 pounds.” These four data values are thevalues for the four variables as applied to Bill Jones
Data:The set of values collected from the variable from each of the elements thatbelong to the sample
The set of 25 heights collected from 25 students is an example of a set of data
Experiment:A planned activity whose results yield a set of data
An experiment includes the activities for both selecting the elements andobtaining the data values
Parameter: A numerical value summarizing all the data of an entire population
The “average” age at time of admission for all students who have ever tended our college and the “proportion” of students who were older than 21years of age when they entered college are examples of two population pa-rameters A parameter is a value that describes the entire population Often a
at-DID YOU KNOW
Just a Jiffy
used in computer engineering
If you’re going to eat your
breakfast in a jiffy then you’ll
have to do it in 10 milliseconds
(0.01 second)!
Trang 39Greek letter is used to symbolize the name of a parameter These symbols will
be assigned as we study specific parameters
For every parameter there is a corresponding sample statistic The statistic
de-scribes the sample the same way the parameter dede-scribes the population
Statistic:A numerical value summarizing the sample data
The “average” height, found by using the set of 25 heights, is an ple of a sample statistic A statistic is a value that describes a sample Mostsample statistics are found with the aid of formulas and are typically as-signed symbolic names that are letters of the English alphabet (for example,
exam-x, s, and r).
A statistics student is interested in finding out something about the averagedollar value of cars owned by the faculty members of our college Each of theeight terms just described can be identified in this situation
1 The population is the collection of all cars owned by all faculty members
at our college
2 A sample is any subset of that population For example, the cars owned
by members of the mathematics department is a sample
3 The variable is the “dollar value” of each individual car.
4 One data value is the dollar value of a particular car Mr Jones’s car, for
example, is valued at $9400
5 The data are the set of values that correspond to the sample obtained
(9400; 8700; 15,950; )
6 The experiment consists of the methods used to select the cars that form
the sample and to determine the value of each car in the sample It could
be carried out by questioning each member of the mathematics ment, or in other ways
depart-7 The parameter about which we are seeking information is the “average”
value of all cars in the population
8 The statistic that will be found is the “average” value of the cars in the
sample
of people being selected—say, the English department—and therefore a ferent value would be anticipated for the statistic “average value.” The aver-age value for “all faculty-owned cars” would not change, however
dif-There are basically two kinds of variables: (1) variables that result in
quali-tative information and (2) variables that result in quantiquali-tative information.
Qualitative, or attribute, or categorical, variable: A variable that describes orcategorizes an element of a population
population; notice that both words
begin with the letter p A statistic
describes the sample; notice that
both words begin with the letter s.
E X A M P L E 1 5 Applying the Basic Terms
value, whereas statistics vary in
value
Watch a video example at
http://1pass.thomson.com
or on your CD
Trang 40Quantitative, or numerical, variable: A variable that quantifies an element of apopulation.
A sample of four hair-salon customers was surveyed for their “hair color,”
“hometown,” and “level of satisfaction” with the results of their salon ment All three variables are examples of qualitative (attribute) variables, be-cause they describe some characteristic of the person and all people with thesame attribute belong to the same category The data collected were {blonde,brown, black, brown}, {Brighton, Columbus, Albany, Jacksonville}, and {verysatisfied, satisfied, somewhat satisfied}
treat-The “total cost” of textbooks purchased by each student for this semester’sclasses is an example of a quantitative (numerical) variable A sample resulted inthe following data: $238.87, $94.57, $139.24 [To find the “average cost,” simply
for data that result from a quantitative variable
Each of these types of variables (qualitative and quantitative) can be ther subdivided as illustrated in the following diagram
fur-Qualitative variables may be characterized as nominal or ordinal
Nominal variable: A qualitative variable that characterizes (or describes, ornames) an element of a population Not only are arithmetic operations not mean-ingful for data that result from a nominal variable, but an order cannot be assigned
to the categories
In the survey of four hair-salon customers, two of the variables, “hair color”and “hometown,” are examples of nominal variables because both name somecharacteristic of the person and it would be meaningless to find the sample av-
brown)/4 is undefined Furthermore, color of hair and hometown do not have
an order to their categories
Ordinal variable: A qualitative variable that incorporates an ordered position, orranking
In the survey of four hair-salon customers, the variable “level of tion” is an example of an ordinal variable because it does incorporate an or-dered ranking: “Very satisfied” ranks ahead of “satisfied,” which ranks ahead
satisfac-of “somewhat satisfied.” Another illustration satisfac-of an ordinal variable is the
rank-Nominal Ordinal Discrete Variable
Continuous Qualitative, or Attribute
Quantitative, or Numerical