Chapter 2 source of data (f2 acca)

Bộ đề luyện thi môn F2 ACCA Management Accounting Bộ đề luyện thi môn F2 ACCA Management Accounting Bộ đề luyện thi môn F2 ACCA Management Accounting

Chapter 2: Sources of Data Exam

Part 1: Questions

Below are 35 multiple-choice questions on Chapter 2 content Each question may require selecting one correct answer, all that apply, or other formats Students should answer on separate answer sheets

1 A sample of people is taken with the same proportion of individuals in separate age bands

as in the population as a whole This is an example of which type of sampling?

A Cluster sampling

B Random sampling

C Stratified sampling

D Systematic sampling

2 It was decided to take a sample by selecting the 12th item, and thereafter every 20th item This is an example of which type of sampling?

A Random sampling

B Systematic sampling

C Stratified sampling

D Cluster sampling

3 Which of the following statements about stratified sampling is true?

A The sample will not be representative

B Knowledge is needed of each item of the population

C The sample is chosen entirely at random

D The structure of the sample will not reflect that of the population

4 Which of the following statements are true? (Select all that apply)

A Quantitative data are data that cannot be measured

B Continuous data can take on any value

C Population data are data arising as a result of investigating a group of people or objects

D Secondary data are data collected especially for a specific purpose

5 Which of the following is an explanation of quota sampling?

A Every nth member of the population is selected

B All people are interviewed up to a certain quota

C Each element of the population has an equal chance of being chosen

D Every element of one sub-section of the population is selected

6 In which sampling method does every member of the population have an equal chance of being selected?

A Stratified sampling

B Cluster sampling

C Simple random sampling

D Convenience sampling

7 Cluster sampling is most useful when:

A The population is homogeneous

B The population is divided into natural groups like schools or neighborhoods

C We need precise proportions from subgroups

D Time is not a constraint

8 Which of the following is a non-probability sampling method?

A Simple random sampling

B Systematic sampling

C Quota sampling

D Stratified sampling

9 True or False: In systematic sampling, the first item is selected randomly, and then every kth item thereafter

A True

B False

10 Which statement is true about convenience sampling?

A It ensures representativeness

B It is easy and inexpensive but may introduce bias

C It requires a complete list of the population

D It is a type of probability sampling

11 Primary data is:

A Data collected from published reports

B Data gathered specifically for the current research purpose

C Data that has been processed statistically at least once

D Always quantitative in nature

12 Which of the following are examples of qualitative data? (Select all that apply)

A Gender

B Height in centimeters

C Customer satisfaction ratings (e.g., happy, neutral, unhappy)

D Number of sales

13 Continuous data differs from discrete data because:

A Continuous data can take any value within a range

B Discrete data is always whole numbers

C Continuous data cannot be measured

D Discrete data can be fractional

14 Population refers to:

A A subset of the group under study

B The entire group of people or objects about which information is desired

C Only human subjects in a study

D Data that is sampled randomly

15 Secondary data might come from:

A Surveys conducted by the researcher

B Government census reports

C Experiments designed for the study

D Interviews with participants

16 In stratified sampling, the population is divided into:

A Random clusters

B Homogeneous subgroups based on characteristics

C Sequential lists

D Convenient groups

17 Which sampling method might lead to undercoverage bias?

A Simple random sampling

B Telephone surveys during daytime hours

C Stratified sampling

D Systematic sampling

18 Quantitative data can be: (Select all that apply)

A Measured numerically

B Categorical like colors

C Discrete or continuous

D Always primary

19 A researcher selects every 10th student from a school list This is:

A Cluster sampling

B Systematic sampling

C Quota sampling

D Random sampling

20 True or False: Sampling error occurs because we study only a part of the population, not the whole

A True

B False

21 Which is not an advantage of quota sampling?

B Ensures representation of key subgroups

C Every element has equal chance of selection

D Useful when population frame is unavailable

22 Discrete data examples include: (Select all that apply)

A Number of children in a family

B Temperature in degrees Celsius

C Number of cars in a parking lot

D Weight of fruits

23 The main difference between primary and secondary data is:

A Primary is always accurate, secondary is not

B Primary is collected for the specific purpose, secondary is pre-existing

C Primary is quantitative, secondary is qualitative

D Secondary is always from internal sources

24 In cluster sampling, after selecting clusters:

A All elements in selected clusters are sampled

B Only a random subset from each cluster is sampled

C Clusters are stratified further

D It becomes systematic

25 Which statement about random sampling is false?

A It minimizes bias

B It requires a sampling frame

C It guarantees representativeness

D Each element has equal probability

26 Qualitative data is also known as:

A Numerical data

B Categorical data

C Continuous data

D Interval data

27 A census involves:

A Sampling a subset

B Studying the entire population

C Using secondary data only

D Probability sampling

28 Which of the following are sources of secondary data? (Select all that apply)

A Academic journals

B Personal interviews

C Government databases

D Company records from past years

29 Systematic sampling can be problematic if:

A The list is random

B There is a periodic pattern in the population list

C The sample size is large

D It is combined with stratification

30 Continuous data can be measured on a scale and includes:

A Time durations

B Number of votes

C Shoe sizes (if whole numbers)

D Counts of items

31 The purpose of sampling is to:

A Make inferences about the population

B Collect all data possible

C Avoid bias completely

D Use only primary data

32 True or False: Non-probability sampling methods do not allow calculation of sampling error

A True

33 In quota sampling, interviewers:

A Select randomly

B Fill predefined quotas for subgroups

C Cluster groups

D Use systematic intervals

34 Which data type can be ranked but not measured with equal intervals?

A Nominal

B Ordinal

C Interval

D Ratio

35 Population data versus sample data: Population is the complete set, sample is a subset used to estimate True or False?

A True

B False

Part 2: Answers and Detailed Explanations

This section is for instructors Each answer includes an explanation based on fundamental statistical concepts

1 C Stratified sampling Explanation: Sampling with the same proportion of individuals

in age bands as the population is characteristic of stratified sampling, where the pop-ulation is divided into strata and proportional samples are taken from each to ensure representativeness

2 B Systematic sampling Explanation: Selecting the 12th item and every 20th thereafter

is systematic sampling, where a fixed interval is used after a (possibly random) starting point

3 B Knowledge is needed of each item of the population Explanation: Stratified

sampling requires knowledge of population characteristics to classify items into strata, ensuring the sample reflects the population structure

4 B, C Explanation: Quantitative data can be measured; continuous data can take any

value (e.g., height) Population data arise from studying a group The others are false: Quantitative data are measurable, and secondary data are not collected specifically (that’s primary data)

5 B All people are interviewed up to a certain quota Explanation: Quota sampling

involves interviewing until quotas for subgroups are met, often with interviewers choosing conveniently within quotas

6 C Simple random sampling Explanation: Every member has an equal chance in simple

random sampling

7 B The population is divided into natural groups like schools or neighborhoods

Explanation: Cluster sampling is useful when the population has natural groups, selecting

clusters randomly and sampling all or some elements within them

8 C Quota sampling Explanation: Quota sampling is non-probability, based on quotas

rather than random selection

9 A True Explanation: Systematic sampling starts with a random item and selects every

kth item thereafter

10 B It is easy and inexpensive but may introduce bias Explanation: Convenience

sampling selects easily accessible subjects, making it cheap but prone to bias due to non-representativeness

11 B Data gathered specifically for the current research purpose Explanation:

Pri-mary data is collected directly for the current study’s purpose

12 A, C Explanation: Qualitative data are categorical, non-numerical (gender, satisfaction

ratings) Height and sales are quantitative

13 A Continuous data can take any value within a range Explanation: Continuous

data can take any value (e.g., weight), while discrete data are counts or whole numbers

14 B The entire group of people or objects about which information is desired

Explanation: The population is the entire group of interest.

15 B Government census reports Explanation: Secondary data come from existing

sources like government reports

16 B Homogeneous subgroups based on characteristics Explanation: Stratified

sam-pling divides the population into homogeneous strata based on traits (e.g., age, gender)

17 B Telephone surveys during daytime hours Explanation: Daytime surveys may miss

working individuals, causing undercoverage bias

18 A, C Explanation: Quantitative data are numerical, either discrete (counts) or continuous

(measurements)

19 B Systematic sampling Explanation: Selecting every 10th student is systematic

sam-pling

20 A True Explanation: Sampling error arises from studying only a sample, leading to

estimation variability

21 C Every element has equal chance of selection Explanation: Quota sampling is

non-probability and does not ensure equal selection chances

22 A, C Explanation: Discrete data are counts (children, cars) Temperature and weight are

continuous

23 B Primary is collected for the specific purpose, secondary is pre-existing

Ex-planation: This is the key difference; secondary data come from external or prior sources.

24 A All elements in selected clusters are sampled Explanation: Cluster sampling

typically involves sampling all elements in selected clusters

25 C It guarantees representativeness Explanation: Random sampling reduces bias but

does not guarantee representativeness, especially with small samples

26 B Categorical data Explanation: Qualitative data are categorical, non-numerical.

27 B Studying the entire population Explanation: A census studies the entire

popula-tion

28 A, C, D Explanation: Secondary data come from journals, databases, and records

Inter-views are primary

29 B There is a periodic pattern in the population list Explanation: Periodic patterns

aligning with the interval can bias systematic sampling

30 A Time durations Explanation: Time is continuous Votes, shoe sizes (whole), and

counts are discrete

31 A Make inferences about the population Explanation: Sampling aims to infer

pop-ulation characteristics without studying everyone

32 A True Explanation: Non-probability sampling lacks known probabilities, preventing

sampling error calculation

33 B Fill predefined quotas for subgroups Explanation: Interviewers select to meet

subgroup quotas

34 B Ordinal Explanation: Ordinal data can be ranked but lack equal intervals (e.g.,

rank-ings)

35 A True Explanation: The population is the full set, and the sample is a subset for

estimation