TEST BANK
STATISTICS FOR BUSINESS AND
ECONOMICS
,Table of Contents
Chapter 1. Data and Statistics
Chapter 2. Descriptive Statistics: Tabular and Graphical Displays
Chapter 3. Descriptive Statistics: Numerical Measures
Chapter 4. Introduction to Probability
Chapter 5. Discrete Probability Distributions
Chapter 6. Continuous Probability Distributions
Chapter 7. Sampling and Sampling Distributions
Chapter 8. Interval Estimation
Chapter 9. Hypothesis Tests
Chapter 10. Inference About Means and Proportions with Two Populations
Chapter 11. Inferences About Population Variances
Chapter 12. Comparing Multiple Proportions, Test of Independence, and Goodness of Fit
Chapter 13. Experimental Design and Analysis of Variance
Chapter 14. Simple Linear Regression
Chapter 15. Multiple Regression
Chapter 16. Regression Analysis: Model Building
Chapter 17. Time Series Analysis and Forecasting
Chapter 18. Nonparametric Methods
Chapter 19. Decision Analysis
Chapter 20. Index Numbers
Chapter 21. Statistical Methods for Quality Control
Chapter 22. Sample Survey
,CHAPTER 1: DATA AND STATISTICS
EASY LEVEL QUESTIONS (Questions 1–27)
Question 1
What is statistics?
A) The art of making graphs and charts
B) The science of collecting, organizing, analyzing, interpreting, and presenting data
C) A method used exclusively in scientific research
D) A branch of mathematics dealing only with probability
Answer: B
Rationale: Statistics is formally defined as the science of collecting, organizing, analyzing,
interpreting, and presenting data. It serves as a foundation for informed decision-making in
business and economics by transforming raw data into meaningful information.
Question 2
Which of the following best describes a population?
A) A subset of individuals selected from a larger group
B) The complete set of all elements of interest in a study
C) A collection of data points used to make predictions
D) A numerical summary of a sample
Answer: B
Rationale: A population is the complete collection of all elements (individuals, items, or data)
about which we want to make inferences. In contrast, a sample is a subset drawn from this
population. Understanding this distinction is fundamental to statistical analysis.
Question 3
A sample is best described as:
A) The entire group being studied
B) A numerical measure that summarizes population data
,C) A subset of the population selected for analysis
D) A graphical display of data
Answer: C
Rationale: A sample is a portion or subset of the population that is selected for study. Because
studying entire populations is often impractical or too costly, samples are used to make
inferences about the larger population.
Question 4
Which of the following is an example of qualitative data?
A) The weight of a shipment in pounds
B) The number of customers who visited a store
C) The brand of a product purchased by a consumer
D) The temperature recorded at noon each day
Answer: C
Rationale: Qualitative (also called categorical) data refers to data that consist of labels or names
used to identify an attribute of an element. The brand of a product is a category label, making it
qualitative. The other options represent quantitative data because they are numerical
measurements.
Question 5
Which of the following is an example of quantitative data?
A) The color of a car
B) The occupation of a worker
C) The annual revenue of a company in dollars
D) The country of origin of an employee
Answer: C
Rationale: Quantitative data are numerical values that represent quantities. Annual revenue
measured in dollars is a numerical value that allows for arithmetic operations such as addition,
subtraction, and averaging. The other options are categorical labels.
Question 6
A researcher collects data from 200 employees out of a company with 5,000 total employees.
The 5,000 employees represent the:
,A) Sample
B) Statistic
C) Population
D) Parameter
Answer: C
Rationale: The population consists of ALL elements of interest in the study — in this case, all
5,000 employees of the company. The 200 employees selected for study represent the sample
drawn from that population.
Question 7
In the context of statistics, a parameter is:
A) A numerical measure that describes a characteristic of a sample
B) A numerical measure that describes a characteristic of a population
C) Any data point within a dataset
D) A method of collecting data through surveys
Answer: B
Rationale: A parameter is a numerical characteristic of a population, such as the population
mean (μ) or population standard deviation (σ). When the value is calculated from sample data, it
is called a statistic (e.g., the sample mean x̄).
Question 8
Which of the following represents a statistic?
A) The average age of all U.S. citizens
B) The proportion of all voters who support a candidate
C) The average salary calculated from a sample of 50 employees
D) The total number of products manufactured by a factory
Answer: C
Rationale: A statistic is a numerical summary computed from sample data. The average salary
calculated from a sample of 50 employees is derived from a subset of the population, making it a
statistic. Options A and B describe parameters because they refer to entire populations.
Question 9
Which scale of measurement classifies data into categories with no meaningful order?
,A) Ordinal
B) Interval
C) Ratio
D) Nominal
Answer: D
Rationale: The nominal scale simply classifies data into distinct categories without any inherent
ranking or order. Examples include gender, nationality, and color. The ordinal scale has order but
no equal intervals, while interval and ratio scales involve meaningful numerical differences.
Question 10
The ordinal scale of measurement:
A) Has an absolute zero point
B) Allows only for categorization without order
C) Classifies data into categories that can be ranked in a meaningful order
D) Allows for meaningful addition and subtraction of values
Answer: C
Rationale: The ordinal scale ranks categories in a meaningful order, but the differences between
categories are not necessarily equal. For example, customer satisfaction ratings (poor, fair, good,
excellent) can be ordered but we cannot say the difference between "poor" and "fair" is the same
as between "good" and "excellent."
Question 11
Temperature measured on the Fahrenheit scale is an example of which level of measurement?
A) Nominal
B) Ordinal
C) Interval
D) Ratio
Answer: C
Rationale: The Fahrenheit temperature scale is an interval scale because it has equal intervals
between measurements, but it does not have an absolute zero point. A temperature of 0°F does
not mean the absence of heat. Because there is no true zero, ratios are not meaningful (80°F is
not "twice as hot" as 40°F).
,Question 12
Which of the following is the best example of data measured on a ratio scale?
A) Temperature in Celsius
B) IQ scores
C) Class rankings (1st, 2nd, 3rd)
D) A person's height in inches
Answer: D
Rationale: The ratio scale has all the properties of the interval scale plus an absolute
(meaningful) zero point. Height in inches has a true zero (0 inches = no height), meaning ratios
are meaningful. A person who is 72 inches tall is truly twice as tall as someone who is 36 inches
tall.
Question 13
Descriptive statistics refers to:
A) Methods used to draw conclusions about a population based on sample data
B) Tabular, graphical, and numerical methods used to summarize data
C) The collection of data from experimental studies only
D) Statistical methods that use probability to make forecasts
Answer: B
Rationale: Descriptive statistics involves methods for organizing, summarizing, and displaying
data in a meaningful way using tables, graphs, and numerical measures (such as means and
standard deviations). It describes what the data shows without making inferences beyond the data
collected.
Question 14
Statistical inference refers to:
A) Calculating descriptive measures from a population
B) Organizing raw data into tables and charts
C) The process of using sample data to draw conclusions about a population
D) Listing all possible outcomes of an experiment
Answer: C
Rationale: Statistical inference involves using data from a sample to make estimates or test
hypotheses about a population. Because studying entire populations is often impossible or too
expensive, statisticians use inference to generalize from sample results to the broader population.
,Question 15
Which of the following is NOT a source of data for statistical studies?
A) Existing published data sources
B) Statistical studies conducted by others
C) Personal opinions not based on any data
D) Experimental data collected through a designed experiment
Answer: C
Rationale: Personal opinions not based on any systematic data collection are not valid statistical
data sources. Valid sources include existing data (government publications, company databases),
observational studies, surveys, and experimental designs.
Question 16
An element in a dataset refers to:
A) A numerical measure computed from sample data
B) Each individual entity about which data is collected
C) A variable measured on the nominal scale
D) A method of collecting primary data
Answer: B
Rationale: An element (or observation) is the individual entity—such as a person, company, or
product—about which data are collected. A variable is the characteristic being measured, and the
actual values recorded are the data.
Question 17
A variable in a statistical study is:
A) The entity on which data are collected
B) A characteristic or quantity of interest that can take on different values
C) A fixed numerical summary of all elements
D) A graphical display of collected data
Answer: B
Rationale: A variable is a characteristic or attribute that can assume different values for different
elements in a dataset. For example, "salary" is a variable because different employees can have
different salary values. The actual values observed are the data.
,Question 18
Cross-sectional data are:
A) Data collected over multiple time periods for the same variable
B) Data collected on several variables at the same point in time
C) Data gathered exclusively through observational studies
D) Data that measure the same elements at different times
Answer: B
Rationale: Cross-sectional data are collected at a single point in time, providing a "snapshot" of
variables across multiple elements. For example, collecting information about the age, income,
and education of 1,000 people all at once is cross-sectional data.
Question 19
Time series data are:
A) Data collected across multiple elements at the same point in time
B) Data collected from a sample rather than a population
C) Data collected on the same variable at different points in time
D) Data measured only at the ratio level
Answer: C
Rationale: Time series data consist of observations on a variable collected over successive time
periods, such as monthly sales figures over a five-year period. This allows analysts to identify
trends, cycles, and seasonal patterns in the data.
Question 20
Which type of data is collected on many variables for the same set of elements at a single point
in time?
A) Time series data
B) Cross-sectional data
C) Experimental data
D) Qualitative data
Answer: B
Rationale: Cross-sectional data involve collecting information on multiple variables for
numerous elements simultaneously. A business survey collecting data on company size, revenue,
, number of employees, and industry type all at one moment is a classic example of cross-sectional
data.
Question 21
Which of the following best describes a census?
A) Collecting data from a random sample of the population
B) Analyzing data using inferential statistics
C) Collecting data from every element in the population
D) Using data collected in a previous study
Answer: C
Rationale: A census involves collecting data from every element of the population, not just a
subset. While a census provides complete information, it is often extremely expensive and time-
consuming, which is why sampling is frequently preferred in practice.
Question 22
Which of the following is an example of a nominal variable?
A) Number of employees in a company
B) Annual income of a household
C) Marital status (single, married, divorced)
D) Age of a respondent in years
Answer: C
Rationale: Marital status is a nominal variable because it classifies individuals into categories
(single, married, divorced, widowed) that have no inherent numerical order or ranking. The other
options represent numerical (quantitative) measurements.
Question 23
Data obtained from a random sample of people are used to estimate the average household
income in a city. This is an application of:
A) Descriptive statistics
B) Statistical inference
C) Experimental design
D) Nominal measurement
STATISTICS FOR BUSINESS AND
ECONOMICS
,Table of Contents
Chapter 1. Data and Statistics
Chapter 2. Descriptive Statistics: Tabular and Graphical Displays
Chapter 3. Descriptive Statistics: Numerical Measures
Chapter 4. Introduction to Probability
Chapter 5. Discrete Probability Distributions
Chapter 6. Continuous Probability Distributions
Chapter 7. Sampling and Sampling Distributions
Chapter 8. Interval Estimation
Chapter 9. Hypothesis Tests
Chapter 10. Inference About Means and Proportions with Two Populations
Chapter 11. Inferences About Population Variances
Chapter 12. Comparing Multiple Proportions, Test of Independence, and Goodness of Fit
Chapter 13. Experimental Design and Analysis of Variance
Chapter 14. Simple Linear Regression
Chapter 15. Multiple Regression
Chapter 16. Regression Analysis: Model Building
Chapter 17. Time Series Analysis and Forecasting
Chapter 18. Nonparametric Methods
Chapter 19. Decision Analysis
Chapter 20. Index Numbers
Chapter 21. Statistical Methods for Quality Control
Chapter 22. Sample Survey
,CHAPTER 1: DATA AND STATISTICS
EASY LEVEL QUESTIONS (Questions 1–27)
Question 1
What is statistics?
A) The art of making graphs and charts
B) The science of collecting, organizing, analyzing, interpreting, and presenting data
C) A method used exclusively in scientific research
D) A branch of mathematics dealing only with probability
Answer: B
Rationale: Statistics is formally defined as the science of collecting, organizing, analyzing,
interpreting, and presenting data. It serves as a foundation for informed decision-making in
business and economics by transforming raw data into meaningful information.
Question 2
Which of the following best describes a population?
A) A subset of individuals selected from a larger group
B) The complete set of all elements of interest in a study
C) A collection of data points used to make predictions
D) A numerical summary of a sample
Answer: B
Rationale: A population is the complete collection of all elements (individuals, items, or data)
about which we want to make inferences. In contrast, a sample is a subset drawn from this
population. Understanding this distinction is fundamental to statistical analysis.
Question 3
A sample is best described as:
A) The entire group being studied
B) A numerical measure that summarizes population data
,C) A subset of the population selected for analysis
D) A graphical display of data
Answer: C
Rationale: A sample is a portion or subset of the population that is selected for study. Because
studying entire populations is often impractical or too costly, samples are used to make
inferences about the larger population.
Question 4
Which of the following is an example of qualitative data?
A) The weight of a shipment in pounds
B) The number of customers who visited a store
C) The brand of a product purchased by a consumer
D) The temperature recorded at noon each day
Answer: C
Rationale: Qualitative (also called categorical) data refers to data that consist of labels or names
used to identify an attribute of an element. The brand of a product is a category label, making it
qualitative. The other options represent quantitative data because they are numerical
measurements.
Question 5
Which of the following is an example of quantitative data?
A) The color of a car
B) The occupation of a worker
C) The annual revenue of a company in dollars
D) The country of origin of an employee
Answer: C
Rationale: Quantitative data are numerical values that represent quantities. Annual revenue
measured in dollars is a numerical value that allows for arithmetic operations such as addition,
subtraction, and averaging. The other options are categorical labels.
Question 6
A researcher collects data from 200 employees out of a company with 5,000 total employees.
The 5,000 employees represent the:
,A) Sample
B) Statistic
C) Population
D) Parameter
Answer: C
Rationale: The population consists of ALL elements of interest in the study — in this case, all
5,000 employees of the company. The 200 employees selected for study represent the sample
drawn from that population.
Question 7
In the context of statistics, a parameter is:
A) A numerical measure that describes a characteristic of a sample
B) A numerical measure that describes a characteristic of a population
C) Any data point within a dataset
D) A method of collecting data through surveys
Answer: B
Rationale: A parameter is a numerical characteristic of a population, such as the population
mean (μ) or population standard deviation (σ). When the value is calculated from sample data, it
is called a statistic (e.g., the sample mean x̄).
Question 8
Which of the following represents a statistic?
A) The average age of all U.S. citizens
B) The proportion of all voters who support a candidate
C) The average salary calculated from a sample of 50 employees
D) The total number of products manufactured by a factory
Answer: C
Rationale: A statistic is a numerical summary computed from sample data. The average salary
calculated from a sample of 50 employees is derived from a subset of the population, making it a
statistic. Options A and B describe parameters because they refer to entire populations.
Question 9
Which scale of measurement classifies data into categories with no meaningful order?
,A) Ordinal
B) Interval
C) Ratio
D) Nominal
Answer: D
Rationale: The nominal scale simply classifies data into distinct categories without any inherent
ranking or order. Examples include gender, nationality, and color. The ordinal scale has order but
no equal intervals, while interval and ratio scales involve meaningful numerical differences.
Question 10
The ordinal scale of measurement:
A) Has an absolute zero point
B) Allows only for categorization without order
C) Classifies data into categories that can be ranked in a meaningful order
D) Allows for meaningful addition and subtraction of values
Answer: C
Rationale: The ordinal scale ranks categories in a meaningful order, but the differences between
categories are not necessarily equal. For example, customer satisfaction ratings (poor, fair, good,
excellent) can be ordered but we cannot say the difference between "poor" and "fair" is the same
as between "good" and "excellent."
Question 11
Temperature measured on the Fahrenheit scale is an example of which level of measurement?
A) Nominal
B) Ordinal
C) Interval
D) Ratio
Answer: C
Rationale: The Fahrenheit temperature scale is an interval scale because it has equal intervals
between measurements, but it does not have an absolute zero point. A temperature of 0°F does
not mean the absence of heat. Because there is no true zero, ratios are not meaningful (80°F is
not "twice as hot" as 40°F).
,Question 12
Which of the following is the best example of data measured on a ratio scale?
A) Temperature in Celsius
B) IQ scores
C) Class rankings (1st, 2nd, 3rd)
D) A person's height in inches
Answer: D
Rationale: The ratio scale has all the properties of the interval scale plus an absolute
(meaningful) zero point. Height in inches has a true zero (0 inches = no height), meaning ratios
are meaningful. A person who is 72 inches tall is truly twice as tall as someone who is 36 inches
tall.
Question 13
Descriptive statistics refers to:
A) Methods used to draw conclusions about a population based on sample data
B) Tabular, graphical, and numerical methods used to summarize data
C) The collection of data from experimental studies only
D) Statistical methods that use probability to make forecasts
Answer: B
Rationale: Descriptive statistics involves methods for organizing, summarizing, and displaying
data in a meaningful way using tables, graphs, and numerical measures (such as means and
standard deviations). It describes what the data shows without making inferences beyond the data
collected.
Question 14
Statistical inference refers to:
A) Calculating descriptive measures from a population
B) Organizing raw data into tables and charts
C) The process of using sample data to draw conclusions about a population
D) Listing all possible outcomes of an experiment
Answer: C
Rationale: Statistical inference involves using data from a sample to make estimates or test
hypotheses about a population. Because studying entire populations is often impossible or too
expensive, statisticians use inference to generalize from sample results to the broader population.
,Question 15
Which of the following is NOT a source of data for statistical studies?
A) Existing published data sources
B) Statistical studies conducted by others
C) Personal opinions not based on any data
D) Experimental data collected through a designed experiment
Answer: C
Rationale: Personal opinions not based on any systematic data collection are not valid statistical
data sources. Valid sources include existing data (government publications, company databases),
observational studies, surveys, and experimental designs.
Question 16
An element in a dataset refers to:
A) A numerical measure computed from sample data
B) Each individual entity about which data is collected
C) A variable measured on the nominal scale
D) A method of collecting primary data
Answer: B
Rationale: An element (or observation) is the individual entity—such as a person, company, or
product—about which data are collected. A variable is the characteristic being measured, and the
actual values recorded are the data.
Question 17
A variable in a statistical study is:
A) The entity on which data are collected
B) A characteristic or quantity of interest that can take on different values
C) A fixed numerical summary of all elements
D) A graphical display of collected data
Answer: B
Rationale: A variable is a characteristic or attribute that can assume different values for different
elements in a dataset. For example, "salary" is a variable because different employees can have
different salary values. The actual values observed are the data.
,Question 18
Cross-sectional data are:
A) Data collected over multiple time periods for the same variable
B) Data collected on several variables at the same point in time
C) Data gathered exclusively through observational studies
D) Data that measure the same elements at different times
Answer: B
Rationale: Cross-sectional data are collected at a single point in time, providing a "snapshot" of
variables across multiple elements. For example, collecting information about the age, income,
and education of 1,000 people all at once is cross-sectional data.
Question 19
Time series data are:
A) Data collected across multiple elements at the same point in time
B) Data collected from a sample rather than a population
C) Data collected on the same variable at different points in time
D) Data measured only at the ratio level
Answer: C
Rationale: Time series data consist of observations on a variable collected over successive time
periods, such as monthly sales figures over a five-year period. This allows analysts to identify
trends, cycles, and seasonal patterns in the data.
Question 20
Which type of data is collected on many variables for the same set of elements at a single point
in time?
A) Time series data
B) Cross-sectional data
C) Experimental data
D) Qualitative data
Answer: B
Rationale: Cross-sectional data involve collecting information on multiple variables for
numerous elements simultaneously. A business survey collecting data on company size, revenue,
, number of employees, and industry type all at one moment is a classic example of cross-sectional
data.
Question 21
Which of the following best describes a census?
A) Collecting data from a random sample of the population
B) Analyzing data using inferential statistics
C) Collecting data from every element in the population
D) Using data collected in a previous study
Answer: C
Rationale: A census involves collecting data from every element of the population, not just a
subset. While a census provides complete information, it is often extremely expensive and time-
consuming, which is why sampling is frequently preferred in practice.
Question 22
Which of the following is an example of a nominal variable?
A) Number of employees in a company
B) Annual income of a household
C) Marital status (single, married, divorced)
D) Age of a respondent in years
Answer: C
Rationale: Marital status is a nominal variable because it classifies individuals into categories
(single, married, divorced, widowed) that have no inherent numerical order or ranking. The other
options represent numerical (quantitative) measurements.
Question 23
Data obtained from a random sample of people are used to estimate the average household
income in a city. This is an application of:
A) Descriptive statistics
B) Statistical inference
C) Experimental design
D) Nominal measurement
