Business Statistics: A First Course

✍ Scribed by David Levine, Kathryn Szabat, David Stephan

• Publisher: Pearson
• Year: 2019
• Tongue: English
• Leaves: 685
• Edition: 8
• Category: Library

✦ Synopsis

For one-semester business statistics courses.

 

A focus on using statistical methods to analyze and interpret results to make data-informed business decisions

Statistics is essential for all business majors, and Business Statistics: A First Course helps students see the role statistics will play in their own careers by providing examples drawn from all functional areas of business. Guided by the principles set forth by major statistical and business science associations (ASA and DSI), plus the authors’ diverse experiences, the 8th Edition continues to innovate and improve the way this course is taught to all students. With new examples, case scenarios, and problems, the text continues its tradition of focusing on the interpretation of results, evaluation of assumptions, and discussion of next steps that lead to data-informed decision making. The authors feel that this approach, rather than a focus on manual calculations, better serves students in their future careers. This brief offering, created to fit the needs of a one-semester course, is part of the established Berenson/Levine series.

 

Also available with MyLab Business Statistics

By combining trusted author content with digital tools and a flexible platform, MyLab personalizes the learning experience and improves results for each student. For example, with Excel Projects students can organize, analyze, and interpret data, helping them hone their business decision-making skills.

Note: You are purchasing a standalone product; MyLab Business Statistics does not come packaged with this content. Students, if interested in purchasing this title with MyLab Business Statistics, ask your instructor to confirm the correct package ISBN and Course ID. Instructors, contact your Pearson representative for more information.

If you would like to purchase both the physical text and MyLab Business Statistics, search for:

 

0135860202 / 9780135860205 Business Statistics: A First Course Plus MyLab Statistics with Pearson eText -- Access Card Package

 

Package consists of:

• 0135177782 / 9780135177785 Business Statistics: A First Course
• 0135443024 / 9780135443026 MyLab Statistics with Pearson eText -- Standalone Access Card -- for Business Statistics: A First Course

✦ Table of Contents

Cover
Title Page
Copyright Page
About the Authors
Brief Contents
Contents
Preface
First Things First
USING STATISTICS: “The Price of Admission”
FTF.1 Think Differently About Statistics
Statistics: A Way of Thinking
Statistics: An Important Part of Your Business Education
FTF.2 Business Analytics: The Changing Face of Statistics
“Big Data”
FTF.3 Starting Point for Learning Statistics
Statistic
Can Statistics (pl., statistic) Lie?
FTF.4 Starting Point for Using Software
Using Software Properly
REFERENCES
KEY TERMS
EXCEL GUIDE
EG.1 Getting Started with Excel
EG.2 Entering Data
EG.3 Open or Save a Workbook
EG.4 Working with a Workbook
EG.5 Print a Worksheet
EG.6 Reviewing Worksheets
EG.7 If You use the Workbook Instructions
JMP GUIDE
JG.1 Getting Started With Jmp
JG.2 Entering Data
JG.3 Create New Project or Data Table
JG.4 Open or Save Files
JG.5 Print Data Tables or Report Windows
JG.6 Jmp Script Files
MINITAB GUIDE
MG.1 Getting Started with Minitab
MG.2 Entering Data
MG.3 Open or Save Files
MG.4 Insert or Copy Worksheets
MG.5 Print Worksheets
TABLEAU GUIDE
TG.1 Getting Started with Tableau
TG.2 Entering Data
TG.3 Open or Save a Workbook
TG.4 Working with Data
TG.5 Print a Workbook
1 Defining and Collecting Data
USING STATISTICS: Defining Moments
1.1 Defining Variables
Classifying Variables by Type
Measurement Scales
1.2 Collecting Data
Populations and Samples
Data Sources
1.3 Types of Sampling Methods
Simple Random Sample
Systematic Sample
Stratified Sample
Cluster Sample
1.4 Data Cleaning
Invalid Variable Values
Coding Errors
Data Integration Errors
Missing Values
Algorithmic Cleaning of Extreme Numerical Values
1.5 Other Data Preprocessing Tasks
Data Formatting
Stacking and Unstacking Data
Recoding Variables
1.6 Types of Survey Errors
Coverage Error
Nonresponse Error
Sampling Error
Measurement Error
Ethical Issues About Surveys
CONSIDER THIS: New Media Surveys/Old Survey Errors
USING STATISTICS: Defining Moments, Revisited
SUMMARY
REFERENCES
KEY TERMS
CHECKING YOUR UNDERSTANDING
CHAPTER REVIEW PROBLEMS
CASES FOR Chapter 1
Managing Ashland MultiComm Services
CardioGood Fitness
Clear Mountain State Student Survey
Learning with the Digital Cases
Chapter 1 EXCEL GUIDE
EG1.1 Defining Variables
EG1.2 Collecting Data
EG1.3 Types of Sampling Methods
EG1.4 Data Cleaning
EG1.5 Other Data Preprocessing
Chapter 1 JMP GUIDE
JG1.1 Defining Variables
JG1.2 Collecting Data
JG1.3 Types of Sampling Methods
JG1.4 Data Cleaning
JG1.5 Other Preprocessing Tasks
Chapter 1 MINITAB GUIDE
MG1.1 Defining Variables
MG1.2 Collecting Data
MG1.3 Types of Sampling Methods
MG1.4 Data Cleaning
MG1.5 Other Preprocessing Tasks
Chapter 1 TABLEAU GUIDE
TG1.1 Defining Variables
TG1.2 Collecting Data
TG1.3 Types of Sampling Methods
TG1.4 Data Cleaning
TG1.5 Other Preprocessing Tasks
2 Organizing and Visualizing Variables
USING STATISTICS: “The Choice Is Yours”
2.1 Organizing Categorical Variables
The Summary Table
The Contingency Table
2.2 Organizing Numerical Variables
The Frequency Distribution
The Relative Frequency Distribution and the Percentage Distribution
The Cumulative Distribution
2.3 Visualizing Categorical Variables
The Bar Chart
The Pie Chart and the Doughnut Chart
The Pareto Chart
Visualizing Two Categorical Variables
2.4 Visualizing Numerical Variables
The Stem-and-Leaf Display
The Histogram
The Percentage Polygon
The Cumulative Percentage Polygon (Ogive)
2.5 Visualizing Two Numerical Variables
The Scatter Plot
The Time-Series Plot
2.6 Organizing a Mix of Variables
Drill-down
2.7 Visualizing a Mix of Variables
Colored Scatter Plot
Bubble Charts
PivotChart (Excel)
Treemap (Excel, JMP, Tableau)
Sparklines (Excel, Tableau)
2.8 Filtering and Querying Data
Excel Slicers
2.9 Pitfalls in Organizing and Visualizing Variables
Obscuring Data
Creating False Impressions
Chartjunk
USING STATISTICS: “The Choice Is Yours,” Revisited
SUMMARY
REFERENCES
KEY EQUATIONS
KEY TERMS
CHECKING YOUR UNDERSTANDING
CHAPTER REVIEW PROBLEMS
CASES for Chapter 2
Managing Ashland MultiComm Services
Digital Case
CardioGood Fitness
The Choice Is Yours Follow-Up
Clear Mountain State Student Survey
Chapter 2 EXCEL GUIDE
EG2.1 Organizing Categorical Variables
EG2.2 Organizing Numerical Variables
EG2 Charts Group Reference
EG2.3 Visualizing Categorical Variables
EG2.4 Visualizing Numerical Variables
EG2.5 Visualizing Two Numerical Variables
EG2.6 Organizing a Mix of Variables
EG2.7 Visualizing a Mix of Variables
EG2.8 Filtering and Querying Data
Chapter 2 JMP GUIDE
JG2 JMP Choices for Creating Summaries
JG2.1 Organizing Categorical Variables
JG2.2 Organizing Numerical Variables
JG2.3 Visualizing Categorical Variables
JG2.4 Visualizing Numerical Variables
JG2.5 Visualizing Two Numerical Variables
JG2.6 Organizing a Mix of Variables
JG2.7 Visualizing a Mix of Variables
JG2.8 Filtering and Querying Data
JMP Guide Gallery
Chapter 2 MINITAB GUIDE
MG2.1 Organizing Categorical Variables
MG2.2 Organizing Numerical Variables
MG2.3 Visualizing Categorical Variables
MG2.4 Visualizing Numerical Variables
MG2.5 Visualizing Two Numerical Variables
MG2.6 Organizing a Mix of Variables
MG2.7 Visualizing a Mix of Variables
MG2.8 Filtering and Querying Data
Chapter 2 TABLEAU GUIDE
TG2.1 Organizing Categorical Variables
TG2.2 Organizing Numerical Variables
TG2.3 Visualizing Categorical Variables
TG2.4 Visualizing Numerical Variables
TG2.5 Visualizing Two Numerical Variables
TG2.6 Organizing a Mix of Variables
TG2.7 Visualizing a Mix of Variables
3 Numerical Descriptive Measures
USING STATISTICS: More Descriptive Choices
3.1 Measures of Central Tendency
The Mean
The Median
The Mode
3.2 Measures of Variation and Shape
The Range
The Variance and the Standard Deviation
The Coefficient of Variation
Z Scores
Shape: Skewness
Shape: Kurtosis
3.3 Exploring Numerical Variables
Quartiles
The Interquartile Range
The Five-Number Summary
The Boxplot
3.4 Numerical Descriptive Measures for a Population
The Population Mean
The Population Variance and Standard Deviation
The Empirical Rule
Chebyshev’s Theorem
3.5 The Covariance and the Coefficient of Correlation
The Covariance
The Coefficient of Correlation
3.6 Descriptive Statistics: Pitfalls and Ethical Issues
USING STATISTICS: More Descriptive Choices, Revisited
SUMMARY
REFERENCES
KEY EQUATIONS
KEY TERMS
CHECKING YOUR UNDERSTANDING
CHAPTER REVIEW PROBLEMS
CASES FOR CHAPTER 3
Managing Ashland MultiComm Services
Digital Case
CardioGood Fitness
More Descriptive Choices Follow-up
Clear Mountain State Student Survey
Chapter 3 EXCEL GUIDE
EG3.1 Measures of Central Tendency
EG3.2 Measures of Variation and Shape
EG3.3 Exploring Numerical Variables
EG3.4 Numerical Descriptive Measures for a Population
EG3.5 The Covariance and the Coefficient of Correlation
Chapter 3 JMP GUIDE
JG3.1 Measures of Central Tendency
JG3.2 Measures of Variation and Shape
JG3.3 Exploring Numerical Variables
JG3.4 Numerical Descriptive Measures for a Population
JG3.5 The Covariance and the Coefficient of Correlation
Chapter 3 MINITAB GUIDE
MG3.1 Measures of Central Tendency
MG3.2 Measures of Variation and Shape
MG3.3 Exploring Numerical Variables
MG3.4 Numerical Descriptive Measures for a Population
MG3.5 The Covariance and the Coefficient of Correlation
Chapter 3 TABLEAU GUIDE
TG3.3 Exploring Numerical Variables
4 Basic Probability
USING STATISTICS: Possibilities at M&R Electronics World
4.1 Basic Probability Concepts
Events and Sample Spaces
Types of Probability
Summarizing Sample Spaces
Simple Probability
Joint Probability
Marginal Probability
General Addition Rule
4.2 Conditional Probability
Calculating Conditional Probabilities
Decision Trees
Independence
Multiplication Rules
Marginal Probability Using the General Multiplication Rule
4.3 Ethical Issues and Probability
4.4 Bayes’ Theorem
CONSIDER THIS: Divine Providence and Spam
4.5 Counting Rules
USING STATISTICS: Possibilities at M&R Electronics World, Revisited
SUMMARY
REFERENCES
KEY EQUATIONS
KEY TERMS
CHECKING YOUR UNDERSTANDING
CHAPTER REVIEW PROBLEMS
CASES FOR CHAPTER 4
Digital Case
CardioGood Fitness
The Choice Is Yours Follow-Up
Clear Mountain State Student Survey
Chapter 4 EXCEL GUIDE
EG4.1 Basic Probability Concepts
EG4.4 Bayes’ Theorem
EG4.5 Counting Rules
Chapter 4 JMP GUIDE
JG4.4 Bayes’ Theorem
Chapter 4 MINITAB GUIDE
MG4.5 Counting Rules
5 Discrete Probability Distributions
USING STATISTICS: Events of Interest at Ricknel Home Centers
5.1 The Probability Distribution for a Discrete Variable
Expected Value of a Discrete Variable
Variance and Standard Deviation of a Discrete Variable
5.2 Binomial Distribution
Histograms for Discrete Variables
Summary Measures for the Binomial Distribution
5.3 Poisson Distribution
USING STATISTICS: Events of Interest, Revisited
SUMMARY
REFERENCES
KEY EQUATIONS
KEY TERMS
CHECKING YOUR UNDERSTANDING
CHAPTER REVIEW PROBLEMS
CASES FOR CHAPTER 5
Managing Ashland MultiComm Services
Digital Case
Chapter 5 EXCEL GUIDE
EG5.1 The Probability Distribution for a Discrete Variable
EG5.2 Binomial Distribution
EG5.3 Poisson Distribution
Chapter 5 JMP GUIDE
JG5.1 The Probability Distribution for a Discrete Variable
JG5.2 Binomial Distribution
JG5.3 Poisson Distribution
Chapter 5 MINITAB GUIDE
MG5.1 The Probability Distribution for a Discrete Variable
MG5.2 Binomial Distribution
MG5.3 Poisson Distribution
6 The Normal Distribution
USING STATISTICS: Normal Load Times at MyTVLab
6.1 Continuous Probability Distributions
6.2 The Normal Distribution
Role of the Mean and the Standard Deviation
Calculating Normal Probabilities
Finding X Values
CONSIDER THIS: What Is Normal?
6.3 Evaluating Normality
Comparing Data Characteristics to Theoretical Properties
Constructing the Normal Probability Plot
USING STATISTICS: Normal Load Times, Revisited
SUMMARY
REFERENCES
KEY EQUATIONS
KEY TERMS
CHECKING YOUR UNDERSTANDING
CHAPTER REVIEW PROBLEMS
CASES FOR CHAPTER 6
Managing Ashland MultiComm Services
CardioGood Fitness
More Descriptive Choices Follow-up
Clear Mountain State Student Survey
Digital Case
Chapter 6 EXCEL GUIDE
EG6.2 The Normal Distribution
EG6.3 Evaluating Normality
Chapter 6 JMP GUIDE
JG6.2 The Normal Distribution
JG6.3 Evaluating Normality
Chapter 6 MINITAB GUIDE
MG6.2 The Normal Distribution
MG6.3 Evaluating Normality
7 Sampling Distributions
USING STATISTICS: Sampling Oxford Cereals
7.1 Sampling Distributions
7.2 Sampling Distribution of the Mean
The Unbiased Property of the Sample Mean
Standard Error of the Mean
Sampling from Normally Distributed Populations
Sampling from Non-normally Distributed Populations—The Central Limit Theorem
VISUAL EXPLORATIONS: Exploring Sampling Distributions
7.3 Sampling Distribution of the Proportion
USING STATISTICS: Sampling Oxford Cereals, Revisited
SUMMARY
REFERENCES
KEY EQUATIONS
KEY TERMS
CHECKING YOUR UNDERSTANDING
CHAPTER REVIEW PROBLEMS
CASES FOR CHAPTER 7
Managing Ashland MultiComm Services
Digital Case
Chapter 7 EXCEL GUIDE
EG7.2 Sampling Distribution of the Mean
Chapter 7 JMP GUIDE
JG7.2 Sampling Distribution of the Mean
Chapter 7 MINITAB GUIDE
MG7.2 Sampling Distribution of the Mean
8 Confidence Interval Estimation
USING STATISTICS: Getting Estimates at Ricknel Home Centers
8.1 Confidence Interval Estimate for the Mean (σ Known)
Sampling Error
Can You Ever Know the Population Standard Deviation?
8.2 Confidence Interval Estimate for the Mean (σ Unknown)
Student’s t Distribution
The Concept of Degrees of Freedom
Properties of the t Distribution
The Confidence Interval Statement
8.3 Confidence Interval Estimate for the Proportion
8.4 Determining Sample Size
Sample Size Determination for the Mean
Sample Size Determination for the Proportion
8.5 Confidence Interval Estimation and Ethical Issues
USING STATISTICS: Getting Estimates at Ricknel Home Centers, Revisited
SUMMARY
REFERENCES
KEY EQUATIONS
KEY TERMS
CHECKING YOUR UNDERSTANDING
CHAPTER REVIEW PROBLEMS
CASES FOR CHAPTER 8
Managing Ashland MultiComm Services
Digital Case
Sure Value Convenience Stores
CardioGood Fitness
More Descriptive Choices Follow-Up
Clear Mountain State Student Survey
Chapter 8 EXCEL GUIDE
EG8.1 Confidence Interval Estimate for the Mean (σ Known)
EG8.2 Confidence Interval Estimate for the Mean (σ Unknown)
EG8.3 Confidence Interval Estimate for the Proportion
EG8.4 Determining Sample Size
Chapter 8 JMP GUIDE
JG8.1 Confidence Interval Estimate for the Mean ( σ Known)
JG8.2 Confidence Interval Estimate for the Mean ( σ Unknown)
JG8.3 Confidence Interval Estimate for the Proportion
JG8.4 Determining Sample Size
Chapter 8 MINITAB GUIDE
MG8.1 Confidence Interval Estimate for the Mean (σ Known)
MG8.2 Confidence Interval Estimate for the Mean (σ Unknown)
MG8.3 Confidence Interval Estimate for the Proportion
MG8.4 Determining Sample Size
9 Fundamentals of Hypothesis Testing: One-Sample Tests
USING STATISTICS: Significant Testing at Oxford Cereals
9.1 Fundamentals of Hypothesis Testing
The Critical Value of the Test Statistic
Regions of Rejection and Nonrejection
Risks in Decision Making Using Hypothesis Testing
Z Test for the Mean (σ Known)
Hypothesis Testing Using the Critical Value Approach
Hypothesis Testing Using the p-Value Approach
A Connection Between Confidence Interval Estimation and Hypothesis Testing
Can You Ever Know the Population Standard Deviation?
9.2 t Test of Hypothesis for the Mean (σ Unknown)
Using the Critical Value Approach
Using the p-Value Approach
Checking the Normality Assumption
9.3 One-Tail Tests
Using the Critical Value Approach
Using the p-Value Approach
9.4 Z Test of Hypothesis for the Proportion
Using the Critical Value Approach
Using the p-Value Approach
9.5 Potential Hypothesis-Testing Pitfalls and Ethical Issues
Important Planning Stage Questions
Statistical Significance Versus Practical Significance
Statistical Insignificance Versus Importance
Reporting of Findings
Ethical Issues
USING STATISTICS: Significant Testing..., Revisited
SUMMARY
REFERENCES
KEY EQUATIONS
KEY TERMS
CHECKING YOUR UNDERSTANDING
CHAPTER REVIEW PROBLEMS
CASES FOR CHAPTER 9
Managing Ashland MultiComm Services
Digital Case
Sure Value Convenience Stores
Chapter 9 EXCEL GUIDE
EG9.1 Fundamentals of Hypothesis Testing
EG9.2 t Test of Hypothesis for the Mean (σ Unknown)
EG9.3 One-Tail Tests
EG9.4 Z Test of Hypothesis for the Proportion
Chapter 9 JMP GUIDE
JG9.1 Fundamentals of Hypothesis Testing
JG9.2 t Test of Hypothesis for the Mean (σ Unknown)
JG9.3 One-Tail Tests
JG9.4 Z Test of Hypothesis for the Proportion
Chapter 9 MINITAB GUIDE
MG9.1 Fundamentals of Hypothesis Testing
MG9.2 t Test of Hypothesis for the Mean (σ Unknown)
MG9.3 One-Tail Tests
MG9.4 Z Test of Hypothesis for the Proportion
10 Two-Sample Tests and One-Way ANOVA
USING STATISTICS I: Differing Means for Selling Streaming Media Players at Arlingtons?
10.1 Comparing the Means of Two Independent Populations
Pooled-Variance t Test for the Difference Between Two Means Assuming Equal Variances
Evaluating the Normality Assumption
Confidence Interval Estimate for the Difference Between Two Means
Separate-Variance t Test for the Difference Between Two Means, Assuming Unequal Variances
CONSIDER THIS: Do People Really Do This?
10.2 Comparing the Means of Two Related Populations
Paired t Test
Confidence Interval Estimate for the Mean Difference
10.3 Comparing the Proportions of Two Independent Populations
Z Test for the Difference Between Two Proportions
Confidence Interval Estimate for the Difference Between Two Proportions
10.4 F Test for the Ratio of Two Variances
USING STATISTICS II: The Means to Find Differences at Arlingtons
10.5 One-Way ANOVA
Analyzing Variation in One-Way ANOVA
F Test for Differences Among More Than Two Means
One-Way ANOVA F Test Assumptions
Levene Test for Homogeneity of Variance
Multiple Comparisons: The Tukey-Kramer Procedure
USING STATISTICS I: Differing Means for Selling, Revisited
USING STATISTICS II: The Means to Find Differences at Arlingtons, Revisited
SUMMARY
REFERENCES
KEY EQUATIONS
KEY TERMS
CHECKING YOUR UNDERSTANDING
CHAPTER REVIEW PROBLEMS
CASES FOR CHAPTER 10
Managing Ashland MultiComm Services
Digital Case
Sure Value Convenience Stores
CardioGood Fitness
More Descriptive Choices Follow-Up
Clear Mountain State Student Survey
Chapter 10 EXCEL GUIDE
EG10.1 Comparing the Means of Two Independent Populations
EG10.2 Comparing the Means of Two Related Populations
EG10.3 Comparing the Proportions of Two Independent Populations
EG10.4 F Test for the Ratio of Two Variances
EG10.5 One-Way Anova
Chapter 10 JMP GUIDE
JG10.1 Comparing the Means of Two Independent Populations
JG10.2 Comparing the Means of Two Related Populations
JG10.3 Comparing the Proportions of Two Independent Populations
JG10.4 F Test for the Ratio of Two Variances
JG10.5 One-Way Anova
Chapter 10 MINITAB GUIDE
MG10.1 Comparing the Means of Two Independent Populations
MG10.2 Comparing the Means of Two Related Populations
MG10.3 Comparing the Proportions of Two Independent Populations
MG10.4 F Test for the Ratio of Two Variances
MG10.5 One-Way Anova
11 Chi-Square Tests
USING STATISTICS: Avoiding Guesswork About Resort Guests
11.1 Chi-Square Test for the Difference Between Two Proportions
11.2 Chi-Square Test for Differences Among More Than Two Proportions
11.3 Chi-Square Test of Independence
USING STATISTICS: Avoiding Guesswork, Revisited
SUMMARY
REFERENCES
KEY EQUATIONS
KEY TERMS
CHECKING YOUR UNDERSTANDING
CHAPTER REVIEW PROBLEMS
CASES FOR CHAPTER 11
Managing Ashland MultiComm Services
PHASE 1
PHASE 2
Digital Case
CardioGood Fitness
Clear Mountain State Student Survey
Chapter 11 EXCEL GUIDE
EG11.1 Chi-Square Test for the Difference Between Two Proportions
EG11.2 Chi-Square Test for Differences Among More Than Two Proportions
EG11.3 Chi-Square Test of Independence
Chapter 11 JMP GUIDE
JG11.1 Chi-Square Test for the Difference Between Two Proportions
JG11.2 Chi-Square Test for Difference Among More Than Two Proportions
JG11.3 Chi-Square Test of Independence
Chapter 11 MINITAB GUIDE
MG11.1 Chi-Square Test for the Difference Between Two Proportions
MG11.2 Chi-Square Test for Differences Among More Than Two Proportions
MG11.3 Chi-Square Test of Independence
12 Simple Linear Regression
USING STATISTICS: Knowing Customers at Sunflowers Apparel
Preliminary Analysis
12.1 Simple Linear Regression Models
12.2 Determining the Simple Linear Regression Equation
The Least-Squares Method
Predictions in Regression Analysis: Interpolation Versus Extrapolation
Calculating the Slope, b1, and the Y Intercept, b0
12.3 Measures of Variation
Computing the Sum of Squares
The Coefficient of Determination
Standard Error of the Estimate
12.4 Assumptions of Regression
12.5 Residual Analysis
Evaluating the Assumptions
12.6 Measuring Autocorrelation: The Durbin-Watson Statistic
Residual Plots to Detect Autocorrelation
The Durbin-Watson Statistic
12.7 Inferences About the Slope and Correlation Coefficient
t Test for the Slope
F Test for the Slope
Confidence Interval Estimate for the Slope
t Test for the Correlation Coefficient
12.8 Estimation of Mean Values and Prediction of Individual Values
The Confidence Interval Estimate for the Mean Response
The Prediction Interval for an Individual Response
12.9 Potential Pitfalls in Regression
USING STATISTICS: Knowing Customers, Revisited
SUMMARY
REFERENCES
KEY EQUATIONS
KEY TERMS
CHECKING YOUR UNDERSTANDING
CHAPTER REVIEW PROBLEMS
CASES FOR CHAPTER 12
Managing Ashland MultiComm Services
Digital Case
Brynne Packaging
Chapter 12 EXCEL GUIDE
EG12.2 Determining the Simple Linear Regression Equation
EG12.3 Measures of Variation
EG12.5 Residual Analysis
EG12.6 Measuring Autocorrelation: the Durbin‐Watson Statistic
EG12.7 Inferences About the Slope and Correlation Coefficient
EG12.8 Estimation of Mean Values and Prediction of Individual Values
Chapter 12 JMP GUIDE
JG12.2 Determining the Simple Linear Regression Equation
JG12.3 Measures of Variation
JG12.5 Residual Analysis
JG12.6 Measuring Autocorrelation: the Durbin‐Watson Statistic
JG12.7 Inferences About the Slope and Correlation Coefficient
JG12.8 Estimation of Mean Values and Prediction of Individual Values
Chapter 12 MINITAB GUIDE
MG12.2 Determining the Simple Linear Regression Equation
MG12.3 Measures of Variation
MG12.5 Residual Analysis
MG12.6 Measuring Autocorrelation: The Durbin‐Watson Statistic
MG12.7 Inferences About the Slope and Correlation Coefficient
MG12.8 Estimation of Mean Values and Prediction of Individual Values
Chapter 12 TABLEAU GUIDE
TG12.2 Determining the Simple Linear Regression Equation
TG12.3 Measures of Variation
13 Multiple Regression
USING STATISTICS: The Multiple Effects of OmniPower Bars
13.1 Developing a Multiple Regression Model
Interpreting the Regression Coefficients
Predicting the Dependent Variable Y
13.2 Evaluating Multiple Regression Models
Coefficient of Multiple Determination, r²
Adjusted r²
F Test for the Significance of the Overall Multiple Regression Model
13.3 Multiple Regression Residual Analysis
13.4 Inferences About the Population Regression Coefficients
Tests of Hypothesis
Confidence Interval Estimation
13.5 Using Dummy Variables and Interaction Terms
Interactions
USING STATISTICS: The Multiple Effects, Revisited
SUMMARY
REFERENCES
KEY EQUATIONS
KEY TERMS
CHECKING YOUR UNDERSTANDING
CHAPTER REVIEW PROBLEMS
CASES FOR CHAPTER 13
Managing Ashland MultiComm Services
Digital Case
CHAPTER 13 EXCEL GUIDE
EG13.1 Developing a Multiple Regression Model
EG13.2 Evaluating Multiple Regression Models
EG13.3 Multiple Regression ‐Residual Analysis
EG13.4 Inferences About the Population Regression Coefficients
EG13.5 Using Dummy Variables and Interaction Terms
CHAPTER 13 JMP GUIDE
JG13.1 Developing a Multiple Regression Model
JG13.2 Evaluating Multiple Regression Models
JG13.3 Multiple Regression Residual Analysis
JG13.4 Inferences About the Population
JG13.5 Using Dummy Variables And Interaction Terms
CHAPTER 13 MINITAB GUIDE
MG13.1 Developing a Multiple Regression Model
MG13.2 Evaluating Multiple Regression Models
MG13.3 Multiple Regression ‐Residual Analysis
MG13.4 Inferences About the Population Regression Coefficients
MG13.5 Using Dummy Variables and Interaction Terms In Regression Models
14 Business Analytics
USING STATISTICS: Back to Arlingtons for the Future
14.1 Business Analytics Categories
Inferential Statistics and Predictive Analytics
Supervised and Unsupervised Methods
CONSIDER THIS: What’s My Major If I Want to Be a Data Miner?
14.2 Descriptive Analytics
Dashboards
Data Dimensionality and Descriptive Analytics
14.3 Predictive Analytics for Prediction
14.4 Predictive Analytics for Classification
14.5 Predictive Analytics for Clustering
14.6 Predictive Analytics for Association
Multidimensional Scaling (MDS)
14.7 Text Analytics
14.8 Prescriptive Analytics
USING STATISTICS: Back to Arlingtons... , Revisited
REFERENCES
KEY EQUATIONS
KEY TERMS
CHECKING YOUR UNDERSTANDING
CHAPTER REVIEW PROBLEMS
CHAPTER 14 SOFTWARE GUIDE
Introduction
SG14.2 Descriptive Analytics
SG14.3 Predictive Analytics for Prediction
SG14.4 Predictive Analytics for Classification
SG14.5 Predictive Analytics for Clustering
SG14.6 Predictive Analytics for Association
Appendices
A. Basic Math Concepts and Symbols
A.1 Operators
A.2 Rules for Arithmetic Operations
A.3 Rules for Algebra: Exponents and Square Roots
A.4 Rules for Logarithms
A.5 Summation Notation
A.6 Greek Alphabet
B. IMPORTANT SOFTWARE SKILLS AND CONCEPTS
B.1 Identifying the Software Version
B.2 Formulas
B.3 Excel Cell References
B.4 Excel Worksheet Formatting
B.5E Excel Chart Formatting
B.5J JMP Chart Formatting
B.5M Minitab Chart Formatting
B.5T Tableau Chart Formatting
B.6 Creating Histograms for Discrete Probability Distributions (Excel)
B.7 Deleting the “Extra” Histogram Bar (Excel)
C. ONLINE RESOURCES
C.1 About the Online Resources for This Book
C.2 Data Files
C.3 Files Integrated With Microsoft Excel
C.4 Supplemental Files
D. CONFIGURING SOFTWARE
D.1 Microsoft Excel Configuration
D.2 JMP Configuration
D.3 Minitab Configuration
D.4 Tableau Configuration
E. TABLE
E.1 Table of Random Numbers
E.2 The Cumulative Standardized Normal Distribution
E.3 Critical Values of t
E.4 Critical Values of X2
E.5 Critical Values of F
E.6 The Standardized Normal Distribution
E.7 Critical Values of the Studentized Range, Q
E.8 Critical Values, dL and dU, of the Durbin-Watson Statistic, D (Critical Values Are One-Sided)
E.9 Control Chart Factors
F. USEFUL KNOWLEDGE
F.1 Keyboard Shortcuts
F.2 Understanding the Nonstatistical Functions
G. SOFTWARE FAQS
G.1 Microsoft Excel FAQs
G.2 PHStat FAQs
G.3 JMP FAQs
G.4 Minitab FAQs
G.5 Tableau FAQs
H. ALL ABOUT PHStat
H.1 What is PHStat?
H.2 Obtaining and Setting Up PHStat
H.3 Using PHStat
H.4 PHStat Procedures, by Category
Self-Test Solutions and Answers to Selected Even-Numbered Problems
Index
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
P
Q
R
S
T
U
V
W
Y
Z
Credits