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by Dean Foster, Robert Stine
Statistics for Business: Decision Making and Analysis, 3rd Edition
Statistics for Business Decision Making and Analysis
About the Authors
Contents
Preface
What’s New in This Edition
Coverage and Organization
Features
Student Resources
Instructor Resources
Technology Resources
Index of Applications
Accounting
Advertising
Agriculture
Automotive
Banking
Business (General)
Company Names
Construction
Consumers
Demographics
Distribution and Operations Management
E-Commerce
Economics
Education
Energy
Environment
Finance and Investments
Food/Drink
Games
Government
Human Resource Management/Personnel
Insurance
Labor
Law
Management
Manufacturing
Marketing
Media and Entertainment
Pharmaceuticals, Medicine, and Health
Quality Control
Real Estate
Salary and Benefits
Sales and Retail
Science
Service Industries
Sports
Surveys and Opinion Polls
Technology
Transportation
Part I Variation
Chapter 1 Introduction
1.1 What Is Statistics?
Variation
Patterns and Models
1.2 Previews
Predicting Employment
Pricing a Car
Chapter 2 Data
Running a Business is Hard Work.
2.1 Data Tables
Rows and Columns
2.2 Categorical and Numerical Data
Measurement Scales
What Do You Think?
2.3 Recoding and Aggregation
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
2.4 Time Series
2.5 Further Attributes of Data
Sources of Data
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Chapter Summary
Key Terms
Objectives
About the Data
Exercises
Mix and Match
True/False
Think About It
Chapter 3 Describing Categorical Data
Consumers Spend Billions of Dollars Online.
3.1 Looking at Data
Variation
Frequency Table
3.2 Charts of Categorical Data
Bar Chart
Pie Chart
What Do You Think?
3.3 The Area Principle
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
3.4 Mode and Median
Chapter Summary
Key Terms
Objectives
About the Data
Exercises
Mix and Match
True/False
Think About It
You Do It
Chapter 4 Describing Numerical Data
A Standard iPhone 6 Comes with 16 Gigabytes (GB) of Memory.
4.1 Summaries of Numerical Variables
Percentiles
What Do You Think?
Averages
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
What Do You Think?
4.2 Histograms
Histograms versus Bar Charts
The White Space Rule
Width of Histogram Intervals
4.3 Boxplots
Combining Boxplots with Histograms
What Do You Think?
4.4 Shape of a Distribution
Modes
Symmetry and Skewness
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
What Do You Think?
Bell-Shaped Distributions and the Empirical Rule
Standardizing
What Do You Think?
4.5 Epilog
Chapter Summary
Key Terms
Objectives
Formulas
Mean (Average)
Variance
Standard Deviation (SD)
Z-Score
Coefficient of Variation
About the Data
Exercises
Mix and Match
True/False
Think About It
You Do It
Chapter 5 Association between Categorical Variables
Busy Web Sites Charge for Running Ads on Their Pages.
5.1 Contingency Tables
Marginal and Conditional Distributions
What Do You Think?
Stacked Bar Charts
Mosaic Plots
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
What Do You Think?
5.2 Lurking Variables and Simpson’s Paradox Lurking Variables and Simpson’s Paradox
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
5.3 Strength of Association
Chi-Squared
What Do You Think?
Cramer’s V
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Chapter Summary
Key Terms
Objectives
Formulas
Chi-Squared
Cramer’s V
About the Data
Exercises
Mix and Match
True/False
Think About It
You Do It
Chapter 6 Association between Quantitative Variables
What Does It Cost To Heat a Home for the Winter?
6.1 Scatterplots
6.2 Association in Scatterplots
Visual Test for Association
What Do You Think?
Describing Association in a Scatterplot
What Do You Think?
6.3 Measuring Association
Covariance
Correlation
What Do You Think?
6.4 Summarizing Association with a Line
Slope-Intercept Form
Lines and Prediction
Nonlinear Patterns
6.5 Spurious Correlation
What Do You Think?
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
6.6 Correlation Matrix
Chapter Summary
Key Terms
Objectives
Formulas
Covariance
Correlation
Expressions Relating Covariance and Correlation
Correlation Line
About the Data
Exercises
Mix and Match
True/False
Think About It
You Do It
Statistics in Action Case: Financial Time Series
Stock Prices
Stock Prices
Some Details: Stock Splits
Stock Returns
Simple Time Series
Histograms
Value at Risk
Case Summary
Key Terms
Formula
Return on an Investment
About the Data
Questions for Thought
Statistics in Action Case: Executive Compensation
Income and Skewness
Log Transformation
Utility for Wealth
Logs and Histograms
Association and Transformations
Case Summary
Key Terms
About the Data
Questions for Thought
Part II Probability
Chapter 7 Probability
Thousands of Customers Dial Toll-Free Telephone Numbers to Get Help.
7.1 From Data to Probability
The Law of Large Numbers
What Do You Think?
7.2 Rules for Probability
Three Essential Rules
The Complement and Addition Rules
An Example
What Do You Think?
7.3 Independent Events
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Boole’s Inequality
Chapter Summary
Key Terms
Objectives
Formulas and Notation
Complement of an Event
Union of Events
Intersection of Events
Boole’s Inequality
Exercises
Mix and Match
True/False
Think About It
You Do It
Chapter 8 Conditional Probability
Education Affects the Income That You Can Expect to Earn.
8.1 From Tables to Probabilities
Joint Probability
Marginal Probability
Conditional Probability
What Do You Think?
What Do You Think?
8.2 Dependent Events
The Multiplication Rule
What Do You Think?
Order Matters
Independence in Venn Diagrams
What Do You Think?
8.3 Organizing Probabilities
Probability Trees
Probability Tables
8.4 Order in Conditional Probabilities
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Bayes’ Rule
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Chapter Summary
Key Terms
Objectives
Formulas
Conditional Probability
Multiplication Rule
Bayes’ Rule
About the Data
Exercises
Mix and Match
True/False
Think About It
You Do It
Chapter 9 Random Variables
Day Trading Is Popular with Young People Around the World.
9.1 Random Variables
Graphs of Random Variables
Random Variables as Models
What Do You Think?
9.2 Properties of Random Variables
Mean of a Random Variable
Expected Value
What Do You Think?
Variance and Standard Deviation
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
9.3 Properties of Expected Values
Adding or Subtracting a Constant
Multiplying by a Constant
What Do You Think?
9.4 Comparing Random Variables
Sharpe Ratio
Chapter Summary
Key Terms
Objectives
Formulas
Mean or Expected Value of a Discrete Random Variable X
Variance of a Discrete Random Variable
Adding a Constant to a Random Variable
Multiplying a Random Variable by a Constant
Adding a Constant and Multiplying by a Constant
Sharpe Ratio of the Random Variable X with Mean μ and Variance σ2
About the Data
Exercises
Mix and Match
True/False
Think About It
You Do It
Chapter 10 Association between Random Variables
The Two Largest Stock Exchanges in the World
10.1 Portfolios and Random Variables
Two Random Variables
Comparisons and the Sharpe Ratio
10.2 Joint Probability Distribution
Independent Random Variables
What Do You Think?
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Dependent Random Variables
10.3 Sums of Random Variables
What Do You Think?
10.4 Dependence Between Random Variables
Covariance
Covariance and Sums
Correlation
Covariance, Correlation, and Independence
10.5 IID Random Variables
IID Data
What Do You Think?
10.6 Weighted Sums
Variance of Differences
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Chapter Summary
Key Terms
Objectives
Formulas
Joint Probability Distribution of Two Random Variables
Multiplication Rule for Expected Values.
Addition Rule for Expected Values of Sums
Addition Rule for Variances of Sums
Covariance Between Random Variables
Correlation Between Random Variables
About the Data
Exercises
Mix and Match
True/False
Think About It
You Do It
Chapter 11 Probability Models for Counts
Pharmaceutical Advertising Appears On Television,
11.1 Random Variables for Counts
Bernoulli Random Variable
Counting Successes
What Do You Think?
11.2 Binomial Model
Assumptions
Finite Populations
11.3 Properties of Binomial Random Variables
Mean and Variance
Binomial Probabilities
Summary
What Do You Think?
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
11.4 Poisson Model
Poisson Random Variable
Poisson Model
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Chapter Summary
Key Terms
Objectives
Formulas
Binomial Random Variable, Y ~ Bi(n, p)
Poisson Random Variable, X ~ Poisson (λ)
Exercises
Mix and Match
True/False
Think About It
You Do It
Chapter 12 The Normal Probability Model
Prices of Stock Plummeted in October 1987.
12.1 Normal Random Variable
Central Limit Theorem
Normal Probability Distribution
Shifts and Scales
12.2 The Normal Model
What Do You Think?
Standardizing
The Empirical Rule, Revisited
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Using Normal Tables
What Do You Think?
12.3 Percentiles
What Do You Think?
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
12.4 Departures from Normality
Normal Quantile Plot
Skewness and Kurtosis
Chapter Summary
Key Terms
Objectives
Formulas
Probability Distribution
Skewness
Kurtosis
About the Data
Exercises
Mix and Match
True/False
Think About It
You Do It
Statistics in Action Case: Managing Financial Risk
Investment Risk
The Dice Game
Dice Investments
Simulation
A Two-Investment Portfolio
Understanding What Happens
Random Variables
Properties of a Portfolio
Volatility Drag
Real Investments
Broader Implications
Case Summary
Key Terms
Questions for Thought
Statistics in Action Case: Modeling Sampling Variation
A Sampling Experiment
A Model for Counts
Using the Model
The Central Limit Theorem
Counting Possibilities
Using a Normal Model
Weighing in Place of Counting
Using Normality
Does It Matter?
Case Summary
Questions for Thought
Part III Inference
Chapter 13 Samples and Surveys
The Claim “Ranked Tops in Initial Quality” Often Appears in Advertisements for New Cars.
13.1 Two Surprising Properties of Samples
Randomization
Sample Size
What Do You Think?
Simple Random Sample
Identifying the Sampling Frame
What Do You Think?
13.2 Variation
Estimating Parameters
Sampling Variation
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
13.3 Alternative Sampling Methods
Stratified and Cluster Samples
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Census
Voluntary Response
Convenience Samples
What Do You Think?
13.4 Questions to Ask
Chapter Summary
Key Terms
Objectives
About the Data
Exercises
Mix and Match
True/False
Think About It
Chapter 14 Sampling Variation and Quality
Delivery Services Love GPS Devices.
14.1 Sampling Distribution of the Mean
Benefits of Averaging
Normal Models
What Do You Think?
Standard Error of the Mean
Sampling Distribution
What Do You Think?
14.2 Control Limits
Type I and Type II Errors
What Do You Think?
Setting the Control Limits
Balancing Type I and Type II Errors
What Do You Think?
14.3 Using a Control Chart
Repeated Testing
Recognizing a Problem
14.4 Control Charts for Variation
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Chapter Summary
Key Terms
Objectives
Formulas
Sampling Distribution
Standard Error of the Mean
Sample Size Condition
Upper and Lower Control Limits
About the Data
Exercises
Mix and Match
True/False
Think About It
You Do It
Chapter 15 Confidence Intervals
The Federal Reserve Says That U.S. Households Have Accumulated Close to $12 Trillion in Outstanding Debt.
15.1 Ranges for Parameters
Confidence Interval for the Proportion
What Do You Think?
Checklist
Assumptions and Conditions
Sample Size
What Do You Think?
15.2 Confidence Interval for the Mean
Student’s t-Distribution
t-Interval for the Mean
Checklist
What Do You Think?
15.3 Interpreting Confidence Intervals
Common Confusions
15.4 Manipulating Confidence Intervals
Combining Confidence Intervals
Changing the Problem
What Do You Think?
15.5 Margin of Error
Determining Sample Size
What Do You Think?
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Chapter Summary
Key Terms
Objectives
Formulas
z-Interval for the Proportion
t-Interval for the Mean
Margin of Error
About the Data
Exercises
Mix and Match
True/False
Think About It
You Do It
Chapter 16 Statistical Tests
Spam Is Annoying. Junk Email Takes Time to Delete, and You Sometimes Mistakenly Throw Out Messages You Want Along with the Junk.
16.1 Concepts of Statistical Tests
Null and Alternative Hypotheses
What Do You Think?
Type I and II Errors
Previous Hypothesis Tests
What Do You Think?
Test Statistic
What Do You Think?
16.2 Testing the Proportion
α Level
z-Test
What Do You Think?
p-Value
Type II Error
Summary
Motivation State The Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize The Results
16.3 Testing The Mean
t-Statistic
t-Test and p-Value
Summary
Motivation State the Question
Method Describe The Data and Select an Approach
Mechanics Do The Analysis
Message Summarize The Results
16.4 Significance Versus Importance
16.5 Confidence Interval or Test?
Chapter Summary
Key Terms
Objectives
Formulas
One-Sided z-Test of a Proportion
One-Sided t-Test of a Mean
About the Data
Exercises
Mix and Match
True/False
Think About It
You Do It
Chapter 17 Comparison
Diets Are Big Business.
17.1 Types of Comparisons
17.2 Data for Comparisons
Experiments
Confounding
What Do You Think?
17.3 Two-Sample z-Test for Proportions
17.4 Two-Sample Confidence Interval for Proportions
Interpreting the Confidence Interval
Checklist
What Do You Think?
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
17.5 two-Sample t-Test
What Do You Think?
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize The Results
17.6 Confidence Interval for the Difference Between Means
Interpreting the Confidence Interval
Checklist (see the two-sample t-test)
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
17.7 Paired Comparisons
Checklist
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Chapter Summary
Key Terms
Objectives
Formulas
Standard Error of the Difference Between Two Sample Means
Two-Sample t-Test for the Difference in Means
Two-Sample Confidence Interval for the Difference in Means
About the Data
Exercises
Mix and Match
True/False
Think About It
You Do It
Chapter 18 Inference for Counts
Online Marketing Allows a Retailer to Customize Sales Pitches.
18.1 Chi-Squared Tests
18.2 Test of Independence
Hypotheses for the chi-squared test
What Do You Think?
Calculating χ2
What Do You Think?
Plots of the Chi-Squared Test of Independence
Conditions
The Chi-Squared Distribution
Getting the p-Value
Summary: Chi-Squared Test of Independence
Connection to Two-Sample Tests
What Do You Think?
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
18.3 General versus Specific Hypotheses
18.4 Tests of Goodness of Fit
Testing for Randomness
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Testing the Fit of a Probability Model
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Chapter Summary
Key Terms
Objectives
Formulas
Degrees of Freedom (d)
Chi-Squared Statistic
About the Data
Exercises
Mix and Match
True/False
Think About It
You Do It
Statistics in Action Case: Rare Events
Rare Events
Clinical Trials
Defaults on Corporate Bonds
Electronic Components
Inference for Rare Events
Rule of Three
Using the Rule of Three
Determining n
Considerations in Finance
Case Summary
Key Terms
Questions for Thought
About the Data
Statistics in Action Case: Data Mining Using Chi-Squared
Managing Inventories
Looking for Association
Chi-squared Test of Association
Equality of Several Proportions
Data Mining
Standardizing with p-values
Related Methods
Case Summary
Key Terms
Questions for Thought
About the Data
Part IV Regression Models
Chapter 19 Linear Patterns
Many Factors Affect the Price of a Commodity.
19.1 Fitting a Line to Data
Equation of a Line
Least Squares
19.2 Interpreting the Fitted Line
Interpreting the Intercept
Interpreting the Slope
What Do You Think?
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
What Do You Think?
19.3 Properties of Residuals
Standard Deviation of the Residuals
19.4 Explaining Variation
Summarizing the Fit of a Line
19.5 Conditions for Simple Regression
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Chapter Summary
Key Terms
Objectives
Formulas
Linear Equation
Slope
Intercept
Fitted Value
Residual
Standard Deviation of the Residuals
r-squared
About the Data
Exercises
Mix and Match
True/False
Think About It
You Do It
Chapter 20 Curved Patterns
The Price of Gasoline Can Be a Painful Reminder of the Laws of Supply and Demand.
20.1 Detecting Nonlinear Patterns
Scatterplots
Residual Plots
20.2 Transformations
20.3 Reciprocal Transformation
What Do You Think?
Comparing Linear and Nonlinear Equations
Visual Comparisons
Substantive Comparison
What Do You Think?
20.4 Logarithm Transformation
Scatterplots and Residual Plots
Comparing Equations
Elasticity
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Chapter Summary
Key Terms
Objectives
About the Data
Exercises
Mix and Match
True/False
Think About It
You Do It
Chapter 21 The Simple Regression Model
Customized Manufacturing Is a Growth Industry in the United States As Businesses Adjust to Worldwide Competition.
21.1 The Simple Regression Model
Linear on Average
Deviations from the Mean
Data-Generating Process
What Do You Think?
21.2 Conditions for the SRM
Modeling Process
What Do You Think?
21.3 Inference in Regression
Standard Errors
Role of Software
Confidence Intervals
Hypothesis Tests
What Do You Think?
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
21.4 Prediction Intervals
Leveraging the SRM
Reliability of Prediction Intervals
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Chapter Summary
Key Terms
Objectives
Formulas
Simple Regression Model
Checklist of Conditions for the Simple Regression Model
Standard Error of the Slope
Standard Error of the Intercept
Standard Error of Prediction
About the Data
Exercises
Mix and Match
True/False
Think About It
You Do It
Chapter 22 Regression Diagnostics
The Internet Has Changed Many Business Models, Generating New Approaches to Retail Marketing, Medical Care, and Service Industries.
22.1 Changing Variation
Fixed Costs, Marginal Costs, and Variable Costs
Detecting Differences in Variation
Consequences of Different Variation
What Do You Think?
Fixing the Problem: Revise the Model
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Comparing Models with Different Responses
22.2 Outliers
Consequences of an Outlier
What Do You Think?
Extrapolating Prediction Intervals
Fixing the Problem: More Information
22.3 Dependent Errors and Time Series
Detecting Dependence Using the Durbin-Watson Statistic
Consequences of Dependence
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Chapter Summary
Key Terms
Objectives
Formulas
Durbin-Watson Statistic
About the Data
Exercises
Mix and Match
True/False
Think About It
You Do It
Chapter 23 Multiple Regression
Expanding Businesses Must Decide Where to Locate New Outlets.
23.1 The Multiple Regression Model
What Do You Think?
23.2 Interpreting Multiple Regression
Scatterplot Matrix
What Do You Think?
R-squared and se
What Do You Think?
Marginal and Partial Slopes
Path Diagram
What Do You Think?
23.3 Checking Conditions
Residual Plots
23.4 Inference in Multiple Regression
Inference for the Model: F-test
What Do You Think?
Inference for One Coefficient
Prediction Intervals
23.5 Steps in Fitting a Multiple Regression
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Chapter Summary
Key Terms
Objectives
Formulas
Estimates of b0, b1 and b2
Adjusted R2
F-statistic
Standard Deviation of Residuals
About the Data
Exercises
Mix and Match
True/False
Think About It
You Do It
Chapter 24 Building Regression Models
Which Explanatory Variables Belong in a Regression Model?
24.1 Identifying Explanatory Variables
The Initial Model
Identifying Other Variables
Adding Explanatory Variables
24.2 Collinearity
Variance Inflation Factor
Signs of Collinearity
What Do You Think?
Remedies for Collinearity
24.3 Removing Explanatory Variables
Motivation State the Question
Method Describe the Data and Select An Approach
Mechanics Do the Analysis
Message Summarize the Results
Motivation State the Question
Method Describe the Data and Select An Approach
Mechanics Do the Analysis
Message Summarize the Results
Chapter Summary
Key Terms
Objectives
Formulas
Standard Error of a Slope in Multiple Regression
Variance Inflation Factor (VIF)
About the Data
Exercises
Mix and Match
True/False
Think About It
You Do It
Chapter 25 Categorical Explanatory Variables
In 2001, Six Women Filed a Lawsuit Against Wal-Mart in Federal Court in San Francisco.
25.1 Two-Sample Comparisons
Confounding Variables
Subsets and Confounding
What Do You Think?
25.2 Analysis of Covariance
Regression on Subsets
Combining Regressions
What Do You Think?
Interpreting Coefficients
What Do You Think?
25.3 Checking Conditions
Checking for Similar Variances
25.4 Interactions and Inference
Interactions and Collinearity
Parallel Fits
What Do You Think?
Motivation State the Question
Method Describe The Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
25.5 Regression with Several Groups
What Do You Think?
Chapter Summary
Key Terms
Objectives
About the Data
Exercises
Mix and Match
True/False
Think About It
You Do It
Chapter 26 Analysis of Variance
At the Dawn of the 20th Century, More Than 10 Million Americans Toiled On Farms, More Than One-Third of the Domestic Workforce.
26.1 Comparing Several Groups
Comparing Groups in Plots
Relating the t-Test to Regression
What Do You Think?
Comparing Several Groups Using Regression
Interpreting the Estimates
ANOVA Regression Model
What Do You Think?
26.2 Inference in Anova Regression Models
Checking Conditions
What Do You Think?
F-Test for the Difference among Means
Understanding the F-Test
Confidence Intervals
26.3 Multiple Comparisons
Tukey Confidence Intervals
Bonferroni Confidence Intervals
What Do You Think?
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
26.4 Groups of Different Size
Chapter Summary
Key Terms
Objectives
Formulas
Notation for Data
Fitted Values and Residuals
Standard Error for the Difference Between Two Means
Tukey Percentiles q.025,n,J
About the Data
Exercises
Mix and Match
True/False
Think About It
You Do It
Chapter 27 Time Series
The Value of Goods Shipped Measures the Health of a Business.
27.1 Decomposing a Time Series
Smoothing
Exponential Smoothing
What Do You Think?
27.2 Regression Models
Polynomial Trends
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Autoregression
Forecasting an Autoregression
What Do You Think?
27.3 Checking the Model
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Motivation State the Question
Method Describe the Data and Select an Approach
Mechanics Do the Analysis
Message Summarize the Results
Chapter Summary
Key Terms
Objectives
Formulas
Durbin-Watson Statistic and Autocorrelation
Exponential Smoothing, Exponentially Weighted Moving Average (EWMA)
About the Data
Exercises
Mix and Match
True/False
Think About It
You Do It
Statistics in Action Case: Analyzing Experiments
A Pricing Experiment
Balanced Experiment
Preliminary Data Analysis
Two-Way Analysis of Variance
Model
Plan for Analysis
Checking the Model
Testing the Factors
Regression Coefficients
Interactions and One-way Anova
Case Summary
Key Terms
Questions for Thought
Statistics in Action Case: Automated Modeling
Preparations
Data for Modeling
Preliminary Analysis: Outliers and Collinearity
Saturated Model
Stepwise Regression
Avoiding Over-fitting
Running Stepwise Regression
Interpreting the Stepwise Model
Related Algorithms
Case Summary
Key Terms
Questions for Thought
Appendix Tables
Answers
Chapter 2
Mix and Match
True/False
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Chapter 3
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Chapter 4
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Chapter 5
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Chapter 6
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Statistics in Action 1–2
Pfizer case
Executive Compensation case
Chapter 7
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True/False
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Chapter 8
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Chapter 9
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Chapter 10
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Chapter 11
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Chapter 12
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True/False
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Statistics in Action 3–4
Dice Simulation
M&Ms
Chapter 13
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Chapter 14
True/False
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You Do It
Chapter 15
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Chapter 16
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Chapter 17
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Chapter 18
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True/False
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Statistics in Action 5–6
Page 484
Page 491
Chapter 19
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Chapter 20
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Chapter 21
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You Do It
Chapter 22
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Chapter 23
Mix and Match
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You Do It
Chapter 24
Mix and Match
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You Do It
Chapter 25
Mix and Match
True/False
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Chapter 26
Mix and Match
True/False
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You Do It
Chapter 27
Mix and Match
True/False
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Statistics in Action 7–8
Answers for Questions, page 814
Answers for Questions, page 821
Credits
Photo Credits
Front Matter
Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Chapter 7
Chapter 8
Chapter 9
Chapter 10
Chapter 11
Chapter 12
Chapter 13
Chapter 14
Chapter 15
Chapter 16
Chapter 17
Chapter 18
Chapter 19
Chapter 20
Chapter 21
Chapter 22
Chapter 23
Chapter 24
Chapter 25
Chapter 26
Chapter 27
Text Credits
Chapter 5
Chapter 9
Back Matter
Subject Index
Numbers
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
P
Q
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S
T
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X
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Statistics for Business Decision Making and Analysis
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