BUSINESS ANALYTICS 4TH Edition By
Jeffrey Camm
,
, Business Analytics, 2e 1
Table of Contents
Chapter 1 Introduction to Business Analytics................................................................................................. 1
Chapter 2 Analytics on Spreadsheets..............................................................................................................19
Chapter 3 Visualizing and Exploring Data.................................................................................................... 37
Chapter 4 Descriptive Statistical Measures.................................................................................................... 68
Chapter 5 Probability Distributions and Data Modeling............................................................................. 99
Chapter 6 Sampling and Estimation............................................................................................................. 119
Chapter 8 Trendlines and Regression Analysis........................................................................................... 163
Chapter 9 Forecasting Techniques................................................................................................................ 185
Chapter 10 Introduction to Data Mining...................................................................................................... 211
Chapter 11 Spreadsheet Modeling and Analysis.........................................................................................229
Chapter 12 Monte Carlo Simulation and Risk Analysis............................................................................. 259
Chapter 14 Applications of Linear Optimization........................................................................................ 297
Chapter 15 Decision Analysis......................................................................................................................... 346
Supplementary Chapter A Nonlinear and Non-Smooth Optimization................................................... 365
Supplementary Chapter B Optimization Models with Uncertainty......................................................... 395
Copyright © 2016 Pearson Education, Inc.
, 2 Chapter 1: Business Analytics
Business Analytics (Evans)
Chapter 1 Introduction to Business Analytics
1) Descriptive analytics:
A) can predict risk and find relationships in data not readily apparent with traditional analyses.
B) helps companies classify their customers into segments to develop specific marketing
campaigns.
C) helps detect hidden patterns in large quantities of data to group data into sets to
predict behavior.
D) can use mathematical techniques with optimization to make decisions that take into
account the uncertainty in the data.
Answer: B
Diff: 1
Blooms: Remember
Topic: Scope of Business Analytics
LO1: Explain and provide examples of descriptive, predictive, and prescriptive analytics.
LO2: Compare and contrast tools for presenting and organizing data
2) A manager at Gampco Inc. wishes to know the company's revenue and profit in its
previous quarter. Which of the following business analytics will help the manager?
A) prescriptive analytics
B) normative analytics
C) descriptive analytics
D) predictive analytics
Answer: C
Diff: 1
Blooms: Apply AACSB:
Analytic Skills
Topic: Scope of Business Analytics
LO1: Explain and provide examples of descriptive, predictive, and prescriptive analytics.
LO2: Describe the major tools and criteria for decision making.
3) Predictive analytics:
A) summarizes data into meaningful charts and reports that can be standardized or customized.
B) identifies the best alternatives to minimize or maximize an objective.
C) uses data to determine a course of action to be executed in a given situation.
D) detects patterns in historical data and extrapolates them forward in
time. Answer: D
Diff: 2
Blooms: Remember
Topic: Scope of Business Analytics
LO1: Explain and provide examples of descriptive, predictive, and prescriptive analytics.
LO2: Compare and contrast tools for presenting and organizing data
Copyright © 2016 Pearson Education, Inc.
Jeffrey Camm
,
, Business Analytics, 2e 1
Table of Contents
Chapter 1 Introduction to Business Analytics................................................................................................. 1
Chapter 2 Analytics on Spreadsheets..............................................................................................................19
Chapter 3 Visualizing and Exploring Data.................................................................................................... 37
Chapter 4 Descriptive Statistical Measures.................................................................................................... 68
Chapter 5 Probability Distributions and Data Modeling............................................................................. 99
Chapter 6 Sampling and Estimation............................................................................................................. 119
Chapter 8 Trendlines and Regression Analysis........................................................................................... 163
Chapter 9 Forecasting Techniques................................................................................................................ 185
Chapter 10 Introduction to Data Mining...................................................................................................... 211
Chapter 11 Spreadsheet Modeling and Analysis.........................................................................................229
Chapter 12 Monte Carlo Simulation and Risk Analysis............................................................................. 259
Chapter 14 Applications of Linear Optimization........................................................................................ 297
Chapter 15 Decision Analysis......................................................................................................................... 346
Supplementary Chapter A Nonlinear and Non-Smooth Optimization................................................... 365
Supplementary Chapter B Optimization Models with Uncertainty......................................................... 395
Copyright © 2016 Pearson Education, Inc.
, 2 Chapter 1: Business Analytics
Business Analytics (Evans)
Chapter 1 Introduction to Business Analytics
1) Descriptive analytics:
A) can predict risk and find relationships in data not readily apparent with traditional analyses.
B) helps companies classify their customers into segments to develop specific marketing
campaigns.
C) helps detect hidden patterns in large quantities of data to group data into sets to
predict behavior.
D) can use mathematical techniques with optimization to make decisions that take into
account the uncertainty in the data.
Answer: B
Diff: 1
Blooms: Remember
Topic: Scope of Business Analytics
LO1: Explain and provide examples of descriptive, predictive, and prescriptive analytics.
LO2: Compare and contrast tools for presenting and organizing data
2) A manager at Gampco Inc. wishes to know the company's revenue and profit in its
previous quarter. Which of the following business analytics will help the manager?
A) prescriptive analytics
B) normative analytics
C) descriptive analytics
D) predictive analytics
Answer: C
Diff: 1
Blooms: Apply AACSB:
Analytic Skills
Topic: Scope of Business Analytics
LO1: Explain and provide examples of descriptive, predictive, and prescriptive analytics.
LO2: Describe the major tools and criteria for decision making.
3) Predictive analytics:
A) summarizes data into meaningful charts and reports that can be standardized or customized.
B) identifies the best alternatives to minimize or maximize an objective.
C) uses data to determine a course of action to be executed in a given situation.
D) detects patterns in historical data and extrapolates them forward in
time. Answer: D
Diff: 2
Blooms: Remember
Topic: Scope of Business Analytics
LO1: Explain and provide examples of descriptive, predictive, and prescriptive analytics.
LO2: Compare and contrast tools for presenting and organizing data
Copyright © 2016 Pearson Education, Inc.
