Practical Business Statistics

Dedication

Preface

• Examples
• Statistical Graphics
• Extensive Development: Reviews and Class Testing
• Writing Style
• Cases
• Organization
• PowerPoint Slides
• Companion Website
• Instructor’s Manual
• Acknowledgments
• To the Student

About the Author

Part I: Introduction and Descriptive Statistics

• Introduction
• Chapter 1: Introduction: Defining the Role of Statistics in Business
  • Abstract
  • 1.1 Why Statistics?
  • 1.2 What is Statistics?
  • 1.3 The Five Basic Activities of Statistics
  • 1.4 Data Mining and Big Data
  • 1.5 What is Probability?
  • 1.6 General Advice
  • 1.7 End-of-Chapter Materials
• Chapter 2: Data Structures: Classifying the Various Types of Data Sets
  • Abstract
  • 2.1 How Many Variables?
  • 2.2 Quantitative Data: Numbers
  • 2.3 Qualitative Data: Categories
  • 2.4 Time-Series and Cross-Sectional Data
  • 2.5 Sources of Data, Including the Internet
  • 2.6 End-of-Chapter Materials
• Chapter 3: Histograms: Looking at the Distribution of Data
  • Abstract
  • 3.1 A List of Data
  • 3.2 Using a Histogram to Display the Frequencies
  • 3.3 Normal Distributions
  • 3.4 Skewed Distributions and Data Transformation
  • 3.5 Bimodal Distributions With Two Groups
  • 3.6 Outliers
  • 3.7 Data Mining With Histograms
  • 3.8 End-of-Chapter Materials
• Chapter 4: Landmark Summaries: Interpreting Typical Values and Percentiles
  • Abstract
  • 4.1 What is The Most Typical Value?
  • 4.2 What Percentile is it?
  • 4.3 End-of-Chapter Materials
• Chapter 5: Variability: Dealing with Diversity
  • Abstract
  • 5.1 The Standard Deviation: The Traditional Choice
  • 5.2 The Range: Quick and Superficial
  • 5.3 The Coefficient of Variation: A Relative Variability Measure
  • 5.4 Effects of Adding to or Rescaling the Data
  • 5.5 End-of-Chapter Materials

Part II: Probability

• Introduction
• Chapter 6: Probability: Understanding Random Situations
  • Abstract
  • 6.1 An Example: is it Behind Door Number 1, Door Number 2, or Door Number 3?
  • 6.2 How Can You Analyze Uncertainty?
  • 6.3 How Likely is An Event?
  • 6.4 How Can You Combine Information About More Than One Event?
  • 6.5 What is the Best Way to Solve Probability Problems?
  • 6.6 End-of-Chapter Materials
• Chapter 7: Random Variables: Working with Uncertain Numbers
  • Abstract
  • 7.1 Discrete Random Variables
  • 7.2 The Binomial Distribution
  • 7.3 The Normal Distribution
  • 7.4 The Normal Approximation to the Binomial
  • 7.5 Two Other Distributions: The Poisson and The Exponential
  • 7.6 End-of-Chapter Materials

Part III: Statistical Inference

• Introduction
• Chapter 8: Random Sampling: Planning Ahead for Data Gathering
  • Abstract
  • 8.1 Populations and Samples
  • 8.2 The Random Sample
  • 8.3 The Sampling Distribution and the Central Limit Theorem
  • 8.4 A Standard Error is an Estimated Standard Deviation
  • 8.5 Other Sampling Methods
  • 8.6 End-of-Chapter Materials
• Chapter 9: Confidence Intervals: Admitting That Estimates Are Not Exact
  • Abstract
  • 9.1 The Confidence Interval for a Population Mean or a Population Percentage
  • 9.2 Assumptions Needed for Validity
  • 9.3 Interpreting a Confidence Interval
  • 9.4 One-Sided Confidence Intervals
  • 9.5 Prediction Intervals
  • 9.6 End-of-Chapter Materials
• Chapter 10: Hypothesis Testing: Deciding Between Reality and Coincidence
  • Abstract
  • 10.1 Hypotheses Are Not Created Equal!
  • 10.2 Testing the Population Mean Against a Known Reference Value: The t-Test
  • 10.3 Interpreting a Hypothesis Test
  • 10.4 One-Sided Testing
  • 10.5 Testing Whether or not a New Observation Comes From the Same Population
  • 10.6 Testing Two Samples
  • 10.7 End-of-Chapter Materials

Part IV: Regression and Time Series

• Introduction
• Chapter 11: Correlation and Regression: Measuring and Predicting Relationships
  • Abstract
  • 11.1 Exploring Relationships Using Scatterplots and Correlations
  • 11.2 Regression: Prediction of One Variable From Another
  • 11.3 End-of-Chapter Materials
• Chapter 12: Multiple Regression: Predicting One Variable From Several Others
  • Abstract
  • 12.1 Interpreting the Results of a Multiple Regression
  • 12.2 Pitfalls and Problems in Multiple Regression
  • 12.3 Dealing With Nonlinear Relationships and Unequal Variability
  • 12.4 Indicator Variables: Predicting From Categories
  • 12.5 End-of-Chapter Materials
• Chapter 13: Report Writing: Communicating the Results of a Multiple Regression
  • Abstract
  • 13.1 How to Organize Your Report
  • 13.2 Hints and Tips
  • 13.3 Example: A Quick Pricing Formula for Customer Inquiries
  • 13.4 End-of-Chapter Materials
• Chapter 14: Time Series: Understanding Changes Over Time
  • Abstract
  • 14.1 An Overview of Time-Series Analysis
  • 14.2 Trend-Seasonal Analysis
  • 14.3 Modeling Cyclic Behavior Using Box-Jenkins ARIMA Processes
  • 14.4 End-of-Chapter Materials

Part V: Methods and Applications

• Introduction
• Chapter 15: ANOVA: Testing for Differences Among Many Samples and Much More
  • Abstract
  • 15.1 Using Box Plots to Look at Many Samples at Once
  • 15.2 The F Test Tells You If the Averages are Significantly Different
  • 15.3 The Least-Significant-Difference Test: Which Pairs are Different?
  • 15.4 More Advanced ANOVA Designs
  • 15.5 End-of-Chapter Materials
• Chapter 16: Nonparametrics: Testing with Ordinal Data or Nonnormal Distributions
  • Abstract
  • 16.1 Testing the Median Against a Known Reference Value
  • 16.2 Testing for Differences in Paired Data
  • 16.3 Testing to See if Two Unpaired Samples are Significantly Different
  • 16.4 End-of-Chapter Materials
• Chapter 17: Chi-Squared Analysis: Testing for Patterns in Qualitative Data
  • Abstract
  • 17.1 Summarizing Qualitative Data by Using Counts and Percentages
  • 17.2 Testing if Population Percentages are Equal to Known Reference Values
  • 17.3 Testing for Association Between Two Qualitative Variables
  • 17.4 End-of-Chapter Materials
• Chapter 18: Quality Control: Recognizing and Managing Variation
  • Abstract
  • 18.1 Processes and Causes of Variation
  • 18.2 Control Charts and How to Read Them
  • 18.3 Charting a Quantitative Measurement with X¯ and R Charts
  • 18.4 Charting the Percent Defective
  • 18.5 End-of-Chapter Materials

Appendix A: Employee Database

Appendix B: Donations Database

Appendix C: Self-Test: Solutions to Selected Problems and Database Exercises

• 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

Appendix D: Statistical Tables

• Table D.5 R² Table: Level 5% Critical Values (Significant)

Glossary

Index