Chapter 1 (introduction to statistics) lecturer

 Often be referred to as categorical data  Nominal or ordinal scale of measurement will be applied to summarize this kind of data  Usually nonnumeric data  Therefore, appropriate sta

Lecturer: DAO MINH ANH

Faculty of Business and Administration Foreign Trade University

Email: anhdm@ftu.edu.vn

 Textbook

Business Mathematics and Statistics – 5th

edition (A Francis)

 References:

- Essentials of Statistics for Business and

Economics – 3rd edition, 2003 (Anderson Sweeney Williams)

- Statistics for Business and Economics – 4th

edition (Paul Newbold)

 Class attendance: 10%

 Group Assignment and presentation: 30%

 Final exam: 60%

 Tracking information: sales, inventory, products being transported, refunded items, customer information (demographic), business performance of suppliers, etc.

 Collecting and analyzing data “Market basket”

 Decision making on:

- Future trend

- Inventory Management

- Customer Relationship Management

I What is statistics?

II Definitions

III Descriptive statistics and Inferential statistics

IV Qualitative and Quantitative data

V Scales of Measurement

- What first appear in your mind when we talk about “statistics”?

interest rates, population, stock market

prices, unemployment…

- In a very general way:

Statistic

s numerical information

 Making sense of numerical information

 Dealing with uncertainty

 In order to make the right decision or

forecast, decision-makers require as much information as possible

 However, after being collected numerical information is under the raw form

impossible to comprehend thoroughly

These information need to be summarized,

organized and analyzed so that important features emerges

 “Statistics is the science of uncertainty”

 In statistics we have to deal with the

question what might be, what could be… not what is

 One task of statistics is to estimate the

level of uncertainty

 E.g: Before bringing a new product to

market, market research survey about the likely level of demand of this product

maybe undertaken?

should the survey cover all potential

buyers (population)?

Absolutely impossible due to the huge costs of time, money, people…

Sampling

 Let’s consider some examples below:

(i) Does the growth rate of money supply influence the inflation rate?

(ii) If the price of a product rise by 5%, what

is the effect on the sales of this product?

- The relationships between variables will

be analyzed in a quantitative way not qualitative way based on the past behaviors of these variables

 Reliable predictions play a key role in management and making decision

 For example: investment decisions must

be made well ahead of the time at which a new product can be brought to market;

 Essentially, forecasts of future values are obtained through the information of past behaviors

 The analysis of this information suggests future trend

 A particular problem for management: making decisions in the condition of

incomplete information

 Therefore, under such circumstances, possible options should be raised and considered

Public accounting firms use

statistical sampling procedures when conducting audits for

their clients

Economics

Economists use statistical

information in making

forecasts about the future of

the economy or some

aspects of it

Electronic point-of-sale scanners

at retail checkout counters are used to collect data for a variety

 Finance

Financial advisors use price-earnings ratios and dividend yields to guide their

investment recommendations

1/ Variable is a characteristic that changes

or varies over time for different individuals

or objects under consideration

2/ Experimental Units (elements) are

items or objects on which measurements are taken

4/ Population is the WHOLE set of all items

or individuals of interest

5/ Sample is an observed subset of

population values

Descriptive Statistics Inferential Statistics

 Descriptive statistics: Methods used to

summarize and describe the main features

of the whole population in quantitative

 Inferential statistics: Procedures used to draw conclusions or inferences about the characteristics of a population from

information obtained from the sample

 Making estimates, testing hypothesis…

 Used when we can not enumerate the

whole population

Sample Population

Sample statistics

(known)

Population parameters

(unknown, but can

be estimated from sample evidence

Inference

 Estimation

◦ e.g., Estimate the population

mean weight using the sample

mean weight

 Hypothesis Testing

◦ e.g., Use sample evidence to test

the claim that the population

mean weight is 120 pounds

Drawing conclusions and/or making decisions concerning a population based on sample results.

Data can be classified as being qualitative

appropriate statistical methods

Depends on whether the data are qualitative or quantitative, we choose the most

appropriate statistical methods

In general, there are more statistical analysis for quantitative data.

In general, there are more statistical analysis for quantitative data.

 Labels or names used to identify an

attribute of each element

 Often be referred to as categorical data

 Nominal or ordinal scale of measurement will be applied to summarize this kind of data

 Usually nonnumeric data

 Therefore, appropriate statistical analyses are rather limited in comparison with

those of quantitative data

 Quantitative data can be described as

data under the numeric form It indicates how many or how much:

 Quantitative data can be described as

data under the numeric form It indicates how many or how much:

There are two types of quantitative data:

E.g

(i)The number of students in a class

(ii)The number of correct answers in a

test

(iii)People’s height, weight; students’ GPA

 Scales of measurement include:

 Scales of measurement include:

 These scales of measurement gradually develop, from the simplest form (nominal scale) to the most sophisticated one

(interval/ratio scale)

Ratio/Interval Scale

Ordinal Scale

Nominal Scale

Highest Level Complete Analysis

Higher Level Mid-level Analysis

Lowest Level Basic Analysis

 Nominal

Data are labels or names used to identify an

attribute of the element

Data are labels or names used to identify an

attribute of the element

A nonnumeric label or numeric code may be used.A nonnumeric label or numeric code may be used.

Students of a university are classified by the

school in which they are enrolled using a

nonnumeric label such as Business,

Humanities, Education, and so on

Alternatively, a numeric code could be used for the school variable (e.g 1 denotes

Business,2 denotes Humanities, 3 denotes

Education, and so on)

Students of a university are classified by the

school in which they are enrolled using a

nonnumeric label such as Business,

Humanities, Education, and so on

Alternatively, a numeric code could be used for the school variable (e.g 1 denotes

Business,2 denotes Humanities, 3 denotes

Education, and so on)

Please state which fuel are you using at home?

A nonnumeric label or numeric code may be used.

A nonnumeric label or numeric code may be used

Students of a university are classified by their class standing using a nonnumeric

label such as Freshman, Sophomore,

Junior, or Senior

Alternatively, a numeric code could be

used for the class standing variable (e.g 1 denotes Freshman, 2 denotes Sophomore, and so on)

Students of a university are classified by their class standing using a nonnumeric

label such as Freshman, Sophomore,

Junior, or Senior

Alternatively, a numeric code could be

used for the class standing variable (e.g 1 denotes Freshman, 2 denotes Sophomore, and so on)

Please order the kind of fuel that is the most favorite one for you?

 Interval

The data have the properties of ordinal data, and

the interval between observations is expressed in

terms of a fixed unit of measure

The data have the properties of ordinal data, and

the interval between observations is expressed in

terms of a fixed unit of measure

Interval data are always numeric.Interval data are always numeric.

There is no zero value that indicates

that nothing exists for the variable at the zero point.

There is no zero value that indicates

that nothing exists for the variable at the zero point.

 Interval

The ratio of two values of interval scale is not

Meaningful because there is no zero value in this scale

The ratio of two values of interval scale is not

Meaningful because there is no zero value in this scale

Example: Melissa has an SAT score of 800,

while Kevin has an SAT score of 400

Melissa scored 400 points more than Kevin

Please state your opinion on customer service at one restaurant?

Not friendly Friendly

Please state your opinion on customer service at one restaurant?

Not friendly Friendly

 Ratio

The data have all the properties of interval data

and the ratio of two values is meaningful

The data have all the properties of interval data

and the ratio of two values is meaningful

Variables such as distance, height, weight, and time use the ratio scale

Variables such as distance, height, weight, and time use the ratio scale

This scale must contain a zero value that indicates

that nothing exists for the variable at the zero point.

This scale must contain a zero value that indicates

that nothing exists for the variable at the zero point.

Melissa’s college record shows 36 credit hours earned, while Kevin’s record shows 72 credit hours earned Kevin has twice as many credit hours earned as Melissa.

Assume that you spend VND 100,000 for your family’s fuel Please distribute this amount for different kinds that you are

Example: there is a survey on FTU’s students Describe them

as quantitative or qualitative, and the scales of measurement

c/ What do you think how much does your part-time job fit your study field?

 Define the issue

◦ what are the purpose and objectives of the

survey?

 Define the population of interest

 Formulate survey questions

◦ make questions clear and unambiguous

◦ use universally-accepted definitions

◦ limit the number of questions

 Pre-test the survey

◦ pilot test with a small group of participants

◦ assess clarity and length

 Determine the sample size and sampling method

 Select Sample and administer the survey

 Closed-end Questions

◦ Select from a short list of defined choices

 A Population is the set of all items or individuals

of interest

◦ Examples: All likely voters in the next election

All parts produced today

All sales receipts for November

 A Sample is a subset of the population

◦ Examples: 1000 voters selected at random for interview

A few parts selected for destructive testing Every 100 th receipt selected for audit

 Less time consuming than a census

 Less costly to administer than a census

 It is possible to obtain statistical results of a sufficiently high precision based on samples.

 Items of the sample are chosen based on known

 Every individual or item from the

population has an equal chance of being selected

 Selection may be with replacement or

without replacement

 Samples can be obtained from a table of random numbers or computer random number generators

 Population divided into subgroups (called

strata) according to some common

 Decide on sample size: n

 Divide frame of N individuals into groups

 Population is divided into several

“clusters,” each representative of the population

 A simple random sample of clusters is selected

◦ All items in the selected clusters can be used, or

items can be chosen from a cluster using another probability sampling technique

Population

divided into

16 clusters Randomly selected

clusters for sample

 There are three kinds of lies…

THANK YOU!

Describe the variable implicit in these 10 items as quantitative or qualitative, and describe the scale of measurement

suppliers

 You have to do a survey on vacation/ summer

holiday of FTU’s students Work with your groups

to create a questionnaire for this assignment.

 It should contain:

- The goal of the survey

- Objects

- Content