Statistics for Business & Economics (with XLSTAT Education Edition Printed Access Card)

Brief Contents
Contents
Preface
About the Authors
Ch 1: Data and Statistics
	1.1: Applications in Business and Economics
	1.2: Data
	1.3: Data Sources
	1.4: Descriptive Statistics
	1.5: Statistical Inference
	1.6: Analytics
	1.7: Big Data and Data Mining
	1.8: Computers and Statistical Analysis
	1.9: Ethical Guidelines for Statistical Practice
	Summary
	Glossary
	Supplementary Exercises
Ch 2: Descriptive Statistics: Tabular and Graphical Displays
	2.1: Summarizing Data for a Categorical Variable
	2.2: Summarizing Data for a Quantitative Variable
	2.3: Summarizing Data for Two Variables Using Tables
	2.4: Summarizing Data for Two Variables Using Graphical Displays
	2.5: Data Visualization: Best Practices in Creating Effective Graphical Displays
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem 1: Pelican Stores
	Case Problem 2: Motion Picture Industry
	Case Problem 3: Queen City
	Appendix 2.1: Using Minitab for Tabular and Graphical Presentations
	Appendix 2.2: Using Excel for Tabular and Graphical Presentations
Ch 3: Descriptive Statistics: Numerical Measures
	3.1: Measures of Location
	3.2: Measures of Variability
	3.3: Measures of Distribution Shape, Relative Location, and Detecting Outliers
	3.4: Five-Number Summaries and Box Plots
	3.5: Measures of Association between Two Variables
	3.6: Data Dashboards: Adding Numerical Measures to Improve Effectiveness
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem 1: Pelican Stores
	Case Problem 2: Motion Picture Industry
	Case Problem 3: Business Schools of Asia-Pacific
	Case Problem 4: Heavenly Chocolates Website Transactions
	Case Problem 5: African Elephant Populations
	Appendix 3.1: Descriptive Statistics Using Minitab
	Appendix 3.2: Descriptive Statistics Using Excel
Ch 4: Introduction to Probability
	4.1: Random Experiments, Counting Rules, and Assigning Probabilities
	4.2: Events and Their Probabilities
	4.3: Some Basic Relationships of Probability
	4.4: Conditional Probability
	4.5: Bayes' Theorem
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem: Hamilton County Judges
Ch 5: Discrete Probability Distributions
	5.1: Random Variables
	5.2: Developing Discrete Probability Distributions
	5.3: Expected Value and Variance
	5.4: Bivariate Distributions, Covariance, and Financial Portfolios
	5.5: Binomial Probability Distribution
	5.6: Poisson Probability Distribution
	5.7: Hypergeometric Probability Distribution
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem: Go Bananas!
	Appendix 5.1: Discrete Probability Distributions with Minitab
	Appendix 5.2: Discrete Probability Distributions with Excel
Ch 6: Continuous Probability Distributions
	6.1: Uniform Probability Distribution
	6.2: Normal Probability Distribution
	6.3: Normal Approximation of Binomial Probabilities
	6.4: Exponential Probability Distribution
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem: Specialty Toys
	Appendix 6.1: Continuous Probability Distributions with Minitab
	Appendix 6.2: Continuous Probability Distributions with Excel
Ch 7: Sampling and Sampling Distributions
	7.1: The Electronics Associates Sampling Problem
	7.2: Selecting a Sample
	7.3: Point Estimation
	7.4: Introduction to Sampling Distributions
	7.5: Sampling Distribution of x
	7.6: Sampling Distribution of p
	7.7: Properties of Point Estimators
	7.8: Other Sampling Methods
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem: Marion Dairies
	Appendix 7.1: The Expected Value and Standard Deviation of x
	Appendix 7.2: Random Sampling with Minitab
	Appendix 7.3: Random Sampling with Excel
Ch 8: Interval Estimation
	8.1: Population Mean: o Known
	8.2: Population Mean: o Unknown
	8.3: Determining the Sample Size
	8.4: Population Proportion
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem 1: Young Professional Magazine
	Case Problem 2: Gulf Real Estate Properties
	Case Problem 3: Metropolitan Research, Inc.
	Appendix 8.1: Interval Estimation with Minitab
	Appendix 8.2: Interval Estimation Using Excel
Ch 9: Hypothesis Tests
	9.1: Developing Null and Alternative Hypotheses
	9.2: Type I and Type II Errors
	9.3: Population Mean: o Known
	9.4: Population Mean: o Unknown
	9.5: Population Proportion
	9.6: Hypothesis Testing and Decision Making
	9.7: Calculating the Probability of Type II Errors
	9.8: Determining the Sample Size for a Hypothesis Test about a Population Mean
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem 1: Quality Associates, Inc.
	Case Problem 2: Ethical Behavior of Business Students at Bayview University
	Appendix 9.1: Hypothesis Testing with Minitab
	Appendix 9.2: Hypothesis Testing with Excel
Ch 10: Inference about Means and Proportions with Two Populations
	10.1: Inferences about the Difference between Two Population Means: o1 and o2 Known
	10.2: Inferences about the Difference between Two Population Means: o1 and o2 Unknown
	10.3: Inferences about the Difference between Two Population Means: Matched Samples
	10.4: Inferences about the Difference between Two Population Proportions
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem: Par, Inc.
	Appendix 10.1: Inferences about Two Populations Using Minitab
	Appendix 10.2: Inferences about Two Populations Using Excel
Ch 11: Inferences about Population Variances
	11.1: Inferences about a Population Variance
	11.2: Inferences about Two Population Variances
	Summary
	Key Formulas
	Supplementary Exercises
	Case Problem: Air Force Training Program
	Appendix 11.1: Population Variances with Minitab
	Appendix 11.2: Population Variances with Excel
Ch 12: Comparing Multiple Proportions, Test of Independence and Goodness of Fit
	12.1: Testing the Equality of Population Proportions for Three or More Populations
	12.2: Test of Independence
	12.3: Goodness of Fit Test
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem: A Bipartisan Agenda for Change
	Appendix 12.1: Chi-Square Tests Using Minitab
	Appendix 12.2: Chi-Square Tests Using Excel
Ch 13: Experimental Design and Analysis of Variance
	13.1: An Introduction to Experimental Design and Analysis of Variance
	13.2: Analysis of Variance and the Completely Randomized Design
	13.3: Multiple Comparison Procedures
	13.4: Randomized Block Design
	13.5: Factorial Experiment
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem 1: Wentworth Medical Center
	Case Problem 2: Compensation for Sales Professionals
	Appendix 13.1: Analysis of Variance with Minitab
	Appendix 13.2: Analysis of Variance with Excel
Ch 14: Simple Linear Regression
	14.1: Simple Linear Regression Model
	14.2: Least Squares Method
	14.3: Coefficient of Determination
	14.4: Model Assumptions
	14.5: Testing for Significance
	14.6: Using the Estimated Regression Equation for Estimation and Prediction
	14.7: Computer Solution
	14.8: Residual Analysis: Validating Model Assumptions
	14.9: Residual Analysis: Outliers and Influential Observations
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem 1: Measuring Stock Market Risk
	Case Problem 2: U.S. Department of Transportation
	Case Problem 3: Selecting a Point-and-Shoot Digital Camera
	Case Problem 4: Finding the Best Car Value
	Case Problem 5: Buckeye Creek Amusement Park
	Appendix 14.1: Calculus-Based Derivation of Least Squares Formulas
	Appendix 14.2: A Test for Significance Using Correlation
	Appendix 14.3: Regression Analysis with Minitab
	Appendix 14.4: Regression Analysis with Excel
Ch 15: Multiple Regression
	15.1: Multiple Regression Model
	15.2: Least Squares Method
	15.3: Multiple Coefficient of Determination
	15.4: Model Assumptions
	15.5: Testing for Significance
	15.6: Using the Estimated Regression Equation for Estimation and Prediction
	15.7: Categorical Independent Variables
	15.8: Residual Analysis
	15.9: Logistic Regression
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem 1: Consumer Research, Inc.
	Case Problem 2: Predicting Winnings for NASCAR Drivers
	Case Problem 3: Finding the Best Car Value
	Appendix 15.1: Multiple Regression with Minitab
	Appendix 15.2: Multiple Regression with Excel
	Appendix 15.3: Logistic Regression with Minitab
Ch 16: Regression Analysis: Model Building
	16.1: General Linear Model
	16.2: Determining When to Add or Delete Variables
	16.3: Analysis of a Larger Problem
	16.4: Variable Selection Procedures
	16.5: Multiple Regression Approach to Experimental Design
	16.6: Autocorrelation and the Durbin-Watson Test
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem 1: Analysis of PGA Tour Statistics
	Case Problem 2: Rating Wines from the Piedmont Region of Italy
	Appendix 16.1: Variable Selection Procedures with Minitab
Ch 17: Time Series Analysis and Forecasting
	17.1: Time Series Patterns
	17.2: Forecast Accuracy
	17.3: Moving Averages and Exponential Smoothing
	17.4: Trend Projection
	17.5: Seasonality and Trend
	17.6: Time Series Decomposition
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Case Problem 1: Forecasting Food and Beverage Sales
	Case Problem 2: Forecasting Lost Sales
	Appendix 17.1: Forecasting with Minitab
	Appendix 17.2: Forecasting with Excel
Ch 18: Nonparametric Methods
	18.1: Sign Test
	18.2: Wilcoxon Signed-Rank Test
	18.3: Mann-Whitney-Wilcoxon Test
	18.4: Kruskal-Wallis Test
	18.5: Rank Correlation
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Appendix 18.1: Nonparametric Methods with Minitab
	Appendix 18.2: Nonparametric Methods with Excel
Ch 19: Statistical Methods for Quality Control
	19.1: Philosophies and Frameworks
	19.2: Statistical Process Control
	19.3: Acceptance Sampling
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
	Appendix 19.1: Control Charts with Minitab
Ch 20: Index Numbers
	20.1: Price Relatives
	20.2: Aggregate Price Indexes
	20.3: Computing an Aggregate Price Index from Price Relatives
	20.4: Some Important Price Indexes
	20.5: Deflating a Series by Price Indexes
	20.6: Price Indexes: Other Considerations
	20.7: Quantity Indexes
	Summary
	Glossary
	Key Formulas
	Supplementary Exercises
Appendixes
	Appendix A: References and Bibliography
	Appendix B: Tables
	Appendix C: Summation Notation
	Appendix D: Self-Test Solutions and Answers to Even-Numbered Exercises
	Appendix E: Microsoft Excel 2013 and Tools for Statistical Analysis
	Appendix F: Computing p-Values Using Minitab and Excel
Index