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INTRODUCTION TO STATISTICS

Total questions: 85

Worksheet time: 48mins

Name
Class
Date
1.

Statistics is defined as:

a)

A study of numbers only

b)

Scientific procedures for collecting, analyzing, summarizing and presenting data

c)

Mathematical equations only

d)

Predicting the weather

2.

Which of the following is NOT part of statistics?

a)

Data collection

b)

Data analysis

c)

Data organization

d)

Manufacturing products

3.

Business statistics is mainly applied to:

a)

Literature

b)

Marketing, operations, finance, HR

c)

Geography

d)

Chemistry

4.

The main branches of statistics are:

a)

Descriptive and Predictive

b)

Descriptive and Inferential

c)

Primary and Secondary

d)

Discrete and Continuous

5.

Descriptive statistics deals with:

a)

Predictions only

b)

Observed data

c)

Unknown populations

d)

Probability theory

6.

Inferential statistics deals with:

a)

Summarizing data only

b)

Making generalizations from samples to populations

c)

Graphical representation only

d)

None of the above

7.

A bar chart showing monthly sales is an example of:

a)

Descriptive statistics

b)

Inferential statistics

c)

Random sampling

d)

Primary data

8.

Predicting next year’s car ownership rate is an example of:

a)

Descriptive

b)

Inferential

c)

Nominal data

d)

Primary data

9.

Data refers to:

a)

Any collected information

b)

Only numbers

c)

Only text

d)

Only graphs

10.

A variable is:

a)

A fixed number

b)

A measurable characteristic

c)

Only an integer

d)

Always continuous

11.

Raw data is:

a)

Processed data

b)

Unprocessed information

c)

Graphical data

d)

Secondary data

12.

Quantitative variables are:

a)

Always words

b)

Numerical values

c)

Colors

d)

Categories

13.

Qualitative variables are:

a)

Numbers

b)

Categories

c)

Heights

d)

Weights

14.

An example of discrete data is:

a)

Height

b)

Distance

c)

Number of students

d)

Weight

15.

An example of continuous data is:

a)

Number of books

b)

Number of cars

c)

Temperature

d)

Number of chairs

16.

Nominal data refers to:

a)

Data with natural order

b)

Categories without order

c)

Numerical data

d)

Samples

17.

Ordinal data refers to:

a)

Categories with order

b)

Numerical data

c)

Continuous data

d)

Raw data

18.

Population in statistics means:

a)

A small group

b)

Entire group of interest

c)

A sample

d)

Raw data

19.

Sample means:

a)

Entire population

b)

A portion of the population

c)

A parameter

d)

A census

20.

Census means:

a)

Collecting from every member of the population

b)

Collecting from a sample

c)

Collecting secondary data

d)

Raw data

21.

A pilot study is:

a)

Full study

b)

Small-scale preliminary study

c)

Data collection method

d)

Graphing data

22.

A parameter refers to:

a)

Sample summary

b)

Population summary

c)

Variable

d)

Statistic

23.

A statistic refers to:

a)

Population summary

b)

Sample summary

c)

Variable

d)

Parameter

24.

Sampling is important because:

a)

Populations are small

b)

Studying full population is impractical

c)

We do not need accuracy

d)

None

25.

Probability sampling means:

a)

Every item has equal chance

b)

Only researcher decides

c)

Convenience-based

d)

Non-random

26.

Advantage of simple random sampling:

a)

Biased

b)

Fair

c)

Needs no frame

d)

Always convenient

27.

Disadvantage of simple random sampling:

a)

Requires frame

b)

Easy

c)

Always biased

d)

Cannot generalize

28.

Systematic sampling means:

a)

Selecting clusters

b)

Selecting every k-th item

c)

Selecting strata

d)

Selecting quotas

29.

Stratified sampling means:

a)

Dividing into strata and sampling

b)

Selecting clusters

c)

Convenience based

d)

Snowballing

30.

Advantage of stratified sampling:

a)

Simple

b)

Ensures group representation

c)

Biased

d)

Costly

31.

Cluster sampling means:

a)

Selecting strata

b)

Selecting entire clusters randomly

c)

Selecting every k-th

d)

Quotas

32.

Multistage sampling means:

a)

Using multiple stages

b)

One stage only

c)

Non-random

d)

Census

33.

Non-random sampling means:

a)

Equal chance

b)

Based on convenience or judgment

c)

Cluster based

d)

Always unbiased

34.

Convenience sampling means:

a)

Based on researcher’s knowledge

b)

Easy access participants

c)

Snowballing

d)

Stratified

35.

Judgmental sampling means:

a)

Snowball

b)

Based on researcher expertise

c)

Quotas

d)

Random

36.

Snowball sampling means:

a)

Referrals by participants

b)

Random clusters

c)

Census

d)

Strata

37.

Quota sampling means:

a)

Random quotas

b)

Selecting to fill quotas

c)

Convenience

d)

Census

38.

Primary data is:

a)

Collected by researcher firsthand

b)

Collected by others

c)

Secondary

d)

Census only

39.

Secondary data is:

a)

Always collected firsthand

b)

Previously collected by others

c)

Raw data

d)

Census

40.

Example of primary data:

a)

Census report

b)

Government publication

c)

Survey responses

d)

Textbook

41.

Example of secondary data:

a)

Survey you conducted

b)

Census data published

c)

Interview

d)

Observation

42.

Face-to-face interview is:

a)

Remote

b)

Online

c)

In-person

d)

None

43.

Advantage of face-to-face interview:

a)

Cheap

b)

High response rate

c)

Anonymous

d)

No training

44.

Disadvantage of face-to-face interview:

a)

Costly and time consuming

b)

Anonymous

c)

Easy

d)

Requires no training

45.

Postal questionnaire is:

a)

Delivered by mail

b)

Face-to-face

c)

Online

d)

Observation

46.

Observation method means:

a)

Watching participants naturally

b)

Asking survey

c)

Reading books

d)

Random sampling

47.

Online survey is:

a)

Postal

b)

Face-to-face

c)

Internet-based

d)

Census

48.

Business analytics is:

a)

Studying literature

b)

Using data for business decisions

c)

Reading books

d)

Chemistry

49.

The four business analytics types include:

a)

Descriptive, Diagnostic, Predictive, Prescriptive

b)

Census, Sample, Parameter, Statistic

c)

Primary, Secondary, Raw, Processed

d)

Nominal, Ordinal, Discrete, Continuous

50.

TensorFlow and PyTorch are frameworks for:

a)

Web development

b)

Game development

c)

Machine learning

d)

Sampling

51.

Statistics only involves numbers

a)

True

b)

False

52.

Descriptive statistics makes predictions

a)

True

b)

False

53.

Inferential statistics uses probability theory

a)

True

b)

False

54.

Raw data is unprocessed information

a)

True

b)

False

55.

Quantitative variables are always continuous

a)

True

b)

False

56.

Population is always smaller than sample

a)

True

b)

False

57.

A census studies the entire population

a)

True

b)

False

58.

A statistic refers to a population measure

a)

True

b)

False

59.

Systematic random sampling selects every k-th item

a)

True

b)

False

60.

Cluster sampling selects all elements within chosen clusters

a)

True

b)

False

61.

Convenience sampling is unbiased

a)

True

b)

False

62.

Primary data is more reliable than secondary data

a)

True

b)

False

63.

Postal questionnaires always have high response rates

a)

True

b)

False

64.

Observation captures actual behavior

a)

True

b)

False

65.

Descriptive, Diagnostic, Predictive, and Prescriptive are types of business analytics

a)

True

b)

False

66.

Statistics helps in collecting, analyzing, (a)   , and presenting data.

67.

The branch of statistics that summarizes datasets is called ______.

4 lines
68.

The branch of statistics that makes predictions is called ______.

4 lines
69.

Information collected during a study is called (a)   .

70.

A measurable characteristic is called a (a)   .

71.

Freshly collected information is known as (a)   .

72.

Data that can be counted is called (a)   .

73.

Data that can take any value within a range is called (a)   .

74.

Categorical data without order is (a)   .

75.

Categorical data with order is (a)   .

76.

The entire group under study is the (a)   .

77.

A smaller group drawn from the population is the (a)   .

78.

Collecting data from every individual is called a (a)   .

79.

A numerical summary from a population is a (a)   .

80.

A numerical summary from a sample is a (a)   .

81.

Selecting every k-th item is called (a)   sampling.

82.

Dividing a population into strata is called (a)   sampling.

83.

Dividing into clusters and selecting entire clusters is called (a)   sampling.

84.

Data collected firsthand by a researcher is (a)   data.

85.

Data collected by others and reused is (a)   data.

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