Test Bank for Business Analytics, 2nd
Edition by Sanjiv Jaggia
TABLE OF CONTENTS
Chapter 1: Introduction to Business Analytics
Chapter 2: Data Management and Wrangling
Chapter 3: Summary Measures
Chapter 4: Data Visualization
Chapter 5: Probability and Probability Distributions
Chapter 6: Statistical Inference
,Chapter 7: Regression Analysis
Chapter 8: More Topics in Regression Analysis
Chapter 9: Logistic Regression
Chapter 10: Forecasting with Time Series Data
Chapter 11: Introduction to Data Mining
Chapter 12: Supervised Data Mining: k-Nearest Neighbors and Naive Bayes
Chapter 13: Supervised Data Mining: Decision Trees
Chapter 14: Unsupervised Data Mining
Chapter 15: Spreadsheet Modeling
Chapter 16: Risk Analysis and Simulation
Chapter 17: Optimization: Linear Programming
Chapter 18: More Applications in Optimization
CHAPTER 1: INTRODUCTION TO BUSINESS ANALYTICS
TRUE/FALSE - Write 'T' if the statement is true and 'F' if the statement is false.
1) The ability to use qualitative reasoning with quantitative tools allows management to
make decisions to improve business performance.
⊚ true
⊚ false
ANS: TRUE
Business analytics allows for the combination of qualitative reasoning with quantitative tools to
identify key business problems and translate them into improved business processes.
2) The use of historical information to predict what could happen in the future describes
prescriptive analytics.
⊚ true
⊚ false
ANS: FALSE
What could happen in the future describes predictive analytics, whereas “what should we do”
describes prescriptive analytics.
3) Data are the compilation of facts, figures, or other contents, both numerical and non-
numerical.
, ⊚ true
⊚ false
ANS: TRUE
The term data is defined as a compilation of facts, figures, or other contents, both numerical and
non-numerical.
4) Generally speaking, it is not feasible to obtain complete population data due to expense
and near impossibility to examine every member of the population.
⊚ true
⊚ false
ANS: TRUE
Obtaining population data is expensive and it is generally impossible to examine every member
of the population.
5) Collecting height data annually on the sample set of participants is an example of time
series data.
⊚ true
⊚ false
ANS: TRUE
Time series data are collected over several time periods on a certain group of people.
6) Structured and unstructured data are only machine generated.
⊚ true
⊚ false
ANS: FALSE
Structured and unstructured data can be both human-generated and machine-generated.
7) Numerical variables are either discrete or continuous.
⊚ true
⊚ false
ANS: TRUE
Numerical variables assume meaningful numerical values and can be categorized as either
discrete or continuous, whereas categorical variables assume names or labels.
8) When each piece of data in a file is separated by a comma, it is called delimiter and the
file is called a comma-spliced file.
⊚ true
⊚ false
ANS: FALSE
The file is called a comma-separated value (CSV) file or comma-delimited file.
, 9) When coding in HTML, <table> is a tag used to provide structure for textual data.
⊚ true
⊚ false
ANS: TRUE
Tags are an effective and efficient way of providing structure to code identifying the beginning
and completion of items such as tables and paragraphs.
10) In XML, tags are not case-sensitive and are interchangeable. For example, <City>and
<city>represent the same pieces of information.
⊚ true
⊚ false
ANS: FALSE
XML is case-sensitive and would view a deviation as two separate data points.
11) Sally created a table that summarizes the dollar amount of last year’s sales for each store.
This is an example of descriptive analytics.
⊚ true
⊚ false
ANS: TRUE
Descriptive analytics refers to gathering, organizing, tabulating, and visualizing data that
summarizes “what has happened?” This includes summarizing financial statistics such as the
total amount of last year’s sales at each store.
12) Social media data, such as Twitter, Facebook, and TicTok are examples of structured
data.
⊚ true
⊚ false
ANS: FALSE
Structured data have a pre-defined, row-column format. Social media data, while it has some
defined structure, does not have the pre-defined, row-column format and therefore are considered
examples of unstructured data.
13) The characteristics marital status and income are examples of observations.
⊚ true
⊚ false
ANS: FALSE
The characteristics marital status and income are examples of variables because a person’s
marital status and income vary from person to person. Observations (records) are data we collect
about variables.
Edition by Sanjiv Jaggia
TABLE OF CONTENTS
Chapter 1: Introduction to Business Analytics
Chapter 2: Data Management and Wrangling
Chapter 3: Summary Measures
Chapter 4: Data Visualization
Chapter 5: Probability and Probability Distributions
Chapter 6: Statistical Inference
,Chapter 7: Regression Analysis
Chapter 8: More Topics in Regression Analysis
Chapter 9: Logistic Regression
Chapter 10: Forecasting with Time Series Data
Chapter 11: Introduction to Data Mining
Chapter 12: Supervised Data Mining: k-Nearest Neighbors and Naive Bayes
Chapter 13: Supervised Data Mining: Decision Trees
Chapter 14: Unsupervised Data Mining
Chapter 15: Spreadsheet Modeling
Chapter 16: Risk Analysis and Simulation
Chapter 17: Optimization: Linear Programming
Chapter 18: More Applications in Optimization
CHAPTER 1: INTRODUCTION TO BUSINESS ANALYTICS
TRUE/FALSE - Write 'T' if the statement is true and 'F' if the statement is false.
1) The ability to use qualitative reasoning with quantitative tools allows management to
make decisions to improve business performance.
⊚ true
⊚ false
ANS: TRUE
Business analytics allows for the combination of qualitative reasoning with quantitative tools to
identify key business problems and translate them into improved business processes.
2) The use of historical information to predict what could happen in the future describes
prescriptive analytics.
⊚ true
⊚ false
ANS: FALSE
What could happen in the future describes predictive analytics, whereas “what should we do”
describes prescriptive analytics.
3) Data are the compilation of facts, figures, or other contents, both numerical and non-
numerical.
, ⊚ true
⊚ false
ANS: TRUE
The term data is defined as a compilation of facts, figures, or other contents, both numerical and
non-numerical.
4) Generally speaking, it is not feasible to obtain complete population data due to expense
and near impossibility to examine every member of the population.
⊚ true
⊚ false
ANS: TRUE
Obtaining population data is expensive and it is generally impossible to examine every member
of the population.
5) Collecting height data annually on the sample set of participants is an example of time
series data.
⊚ true
⊚ false
ANS: TRUE
Time series data are collected over several time periods on a certain group of people.
6) Structured and unstructured data are only machine generated.
⊚ true
⊚ false
ANS: FALSE
Structured and unstructured data can be both human-generated and machine-generated.
7) Numerical variables are either discrete or continuous.
⊚ true
⊚ false
ANS: TRUE
Numerical variables assume meaningful numerical values and can be categorized as either
discrete or continuous, whereas categorical variables assume names or labels.
8) When each piece of data in a file is separated by a comma, it is called delimiter and the
file is called a comma-spliced file.
⊚ true
⊚ false
ANS: FALSE
The file is called a comma-separated value (CSV) file or comma-delimited file.
, 9) When coding in HTML, <table> is a tag used to provide structure for textual data.
⊚ true
⊚ false
ANS: TRUE
Tags are an effective and efficient way of providing structure to code identifying the beginning
and completion of items such as tables and paragraphs.
10) In XML, tags are not case-sensitive and are interchangeable. For example, <City>and
<city>represent the same pieces of information.
⊚ true
⊚ false
ANS: FALSE
XML is case-sensitive and would view a deviation as two separate data points.
11) Sally created a table that summarizes the dollar amount of last year’s sales for each store.
This is an example of descriptive analytics.
⊚ true
⊚ false
ANS: TRUE
Descriptive analytics refers to gathering, organizing, tabulating, and visualizing data that
summarizes “what has happened?” This includes summarizing financial statistics such as the
total amount of last year’s sales at each store.
12) Social media data, such as Twitter, Facebook, and TicTok are examples of structured
data.
⊚ true
⊚ false
ANS: FALSE
Structured data have a pre-defined, row-column format. Social media data, while it has some
defined structure, does not have the pre-defined, row-column format and therefore are considered
examples of unstructured data.
13) The characteristics marital status and income are examples of observations.
⊚ true
⊚ false
ANS: FALSE
The characteristics marital status and income are examples of variables because a person’s
marital status and income vary from person to person. Observations (records) are data we collect
about variables.
