Part 1: BUSINESS STATISTICS: INTRODUCTION AND BACKGROUND 1. A Preview of Business Statistics Introduction Statistics: Yesterday and Today Descriptive Versus Inferential Statistics Types of Variables and Scales of Measurement Statistics in Business Decisions Business Statistics: Tools Versus Tricks Summary 2. Visual Description of Data Introduction The Data Array and the Frequency Distribution The Stem and Leaf Display and the Dotplot Visual Representation of the Data The Scatter Diagram Tabulation, Contingency Tables, and the Excel PivotTable Wizard Summary 3. Statistical Description of Data Introduction Statistical Description: Measures of Central Tendency Statistical Description: Measures of Dispersion Additional Dispersion Topics Descriptive Statistics from Grouped Data Statistical Measures of Association Summary 4. Data Collection and Sampling Methods Introduction Research Basics Survey Research Experimentation and Observational Research Secondary Data The Basics of Sampling Sampling Methods Summary Part 2: PROBABILITY 5. Probability: Review of Basic Concepts Introduction Probability: Terms and Approaches Unions and Intersections of Events Addition Rules for Probability Multiplication Rules for Probability Bayes' Theorem and the Revision of Probabilities Counting: Permutations and Combinations Summary 6. Discrete Probability Distributions Introduction The Binomial Distribution The Poisson Distribution Simulating Observations from a Discrete Probability Distribution Summary 7. Continuous Probability Distributions Introduction The Normal Distribution The Standard Normal Distribution The Normal Approximation to the Binomial Distribution The Exponential Distribution Simulating Observations from a Continuous Probability Distribution Summary Part 3: SAMPLING DISTRIBUTION AND ESTIMATION 8. Sampling Distributions Introduction A Review of Sampling Distributions The Sampling Distribution of the Mean The Sampling Distribution of the Proportion Sampling Distributions When the Population is Finite Computer Simulation of Sampling Distributions Summary 9. Estimation from Simple Data Introduction Point Estimates A Preview of Interval Estimates Confidence Interval Estimates for the Mean: s Known Confidence Interval Estimates for the Mean: s Unknown Confidence Interval Estimates for the Population Proportion Sample Size Determination When the Population is Finite Summary Part 4: HYPOTHESIS TESTING 10. Hypothesis Tests Involving a Simple Mean or Proportion Introduction Hypothesis Testing: Basic Procedures Testing a Mean, Population Standard Deviation Known Confidence Intervals and Hypothesis Testing Testing a Mean, Population Standard Deviation Unknown Testing a Proportion The Power of a Hypothesis Test Summary 11. Hypothesis Tests Involving Two Simple Means or Proportions Introduction The Pooled-Variances t-Test for Comparing the Means of Two Independent Samples The Unequal-Variances t-Test for Comparing the Means of Two Independent Samples The z-Test for Comparing the Means of Two Independent Samples Comparing Two Means When the Samples are Dependent Comparing Two Sample Proportions Comparing the Variances of Two Independent Samples Summary 12. Analysis of Variance Tests Introduction Analysis of Variance: Basic Concepts One-Way Analysis of Variance The Randomized Block Design Two-Way Analysis of Variance Summary 13. Chi-Square Applications Introduction Basic Concepts in Chi-Square Testing Tests for Goodness-of-Fit and Normality Testing the Independence of Two Variables Comparing Proportions from k Independent Samples Estimation and Tests Regarding the Population Variance Summary 14. Nonparametric Methods Introduction Wilcoxon Signed Rank Test for One Sample Wilcoxon Signed Rank Test for Comparing Paired Samples Wilcoxon Rank Sum Test for Comparing Two Independent Samples Kruskal-Wallis Test for Comparing More Than Two Independent Samples Friedman Test for the Randomized Block Design Other Nonparametric Methods Summary Part 5: REGRESSION, MODEL BUILDING, AND TIME SERIES 15. Simple Linear Regression and Correlation Introduction The Simple Linear Regression Model Interval Estimation Using the Sample Regression Line Correlation Analysis Estimation and Tests Regarding the Sample Regression Line Additional Topics in Regression and Correlation Analysis Summary 16. Multiple Regression and Correlation Introduction The Multiple Regression Model Interval Estimation in Multiple Regression Multiple Correlation Analysis Significance Tests in Multiple Regression and Correlation Overview of the Computer Analysis and Interpretation Additional Topics in Multiple Regression and Correlation Summary 17. Model Building Introduction Polynomial Models with One Quantitative Predictor Variable Polynomial Models with Two Quantitative Predictor Variables Qualitative Variables Data Transformations Multicollinearity Stepwise Regression Selecting a Model Summary 18. Time Series, Forecasting and Index Numbers Introduction Time Series Smoothing Techniques Seasonal Indexes Forecasting Evaluating Alternative Models: MAD and MSE Autocorrelation, the Durbin-Watson Test, and Autoregressive Forecasting Index Numbers Summary Part 6: SPECIAL TOPICS 19. Decision Theory Introduction Structuring the Decision Situation Non-Bayesian Decision Making Bayesian Decision Making The Opportunity Loss Approach Incremental Analysis and Inventory Decisions Summary Appendix: The Expected Value of Imperfect Information 20. Total Quality Mangement Introduction A Historical Perspective and Defect Detection The Emergence of Total Quality Management Practicing Total Quality Management Some Statistical Tools for Total Quality Management Statistical Process Control: The Concepts Control Charts for Variables Control Charts for Attributes More on Computer-Assisted Statistical Process Control Summary