Introduction to Modern Business Statistics

1. INTRODUCTION TO STATISTICS AND STATISTICAL THINKING Introduction / The Fundamental Elements of Statistical Analysis / The Evaluation of Statistical Analyses / Obtaining Data / Statistical Thinking for Process Management and Quality Improvement / An Introduction to the Design of Experiments / Statistical Notation / Use of Computers in Statistical Analysis / Looking Ahead / Summary / Appendix 1: Introduction to MINITAB, Excel, and JMP IN 2. EXPLORING AND SUMMARIZING DATA Introduction / Types of Data / Distributions of Data / Measures of Location: The Center of the Data / Measures of Variation / Measures of Relative Standing / Relationships Between Two Variables / Exploring and Summarizing Data: A Comprehensive Example / Summary / Appendix 2A: Computer Instructions for Using MINITAB, Excel, and JMP IN / Appendix 2B: Your Turn to Perform a Statistical Study 3. PROBABILITY, RANDOM VARIABLES, AND PROBABILITY DISTRIBUTIONS Bridging to New Topics / The Basic Elements of Probability / Interpretations and Fundamental Rules of Probabilities / Discrete and Continuous Random Variables / Probability Distributions of Discrete Random Variables / Probability Distributions of Continuous Random Variables / Expected Values of Random Variables / Summary / Appendix 3: Calculus-Based Introduction to Probability Distributions for Continuous Random Variables 4. SOME IMPORTANT PROBABILITY DISTRIBUTIONS Bridging to New Topics / The Binomial Distribution / The Normal Distribution / The Normal Distribution as an Approximation to the Binomial Distribution / Summary / Appendix 4: Computer Instructions for Using MINITAB, Excel, and JMP IN 5. STATISTICS AND SAMPLING DISTRIBUTIONS Bridging to New Topics / Sampling Techniques / Parameters Statistics, and Fundamentals of Statistical Inference / Desirable Properties of Statistics / The Sampling Distribution of the Sample Mean X [overbar] / The Sampling Distribution of the Sample Proportion p / Summary / Appendix 5: Computer Instructions for Using MINITAB, Excel, and JMP IN 6. STATISTICAL INFERENCES FOR A SINGLE POPULATION OR PROCESS Bridging to New Topics / An Introduction to Confidence Intervals and Hypothesis Testing / Statistical Inferences on Mu Based on X [overbar] / Statistical Inference for Pi Based on P / Summary / Appendix 6: Computer Instructions for Using MINITAB and Excel 7. STATISTICAL INFERENCES FOR TWO POPULATIONS OR PROCESSES Bridging to New Topics / Planning a Comparison of Two Means / Statistical Inferences for Two Means Based on Independent Samples / Statistical Inferences for Two Means Based on Paired Samples / Statistical Inferences for Two Proportions Based on Independent Samples / Statistical Inferences for Two Populations or Processes: A Comprehensive Example / Summary / Appendix 7: Computer Instructions for Using MINITAB, Excel, and JMP IN 8. ANALYSIS OF VARIANCE Bridging to New Topics / Comparing More Than Two Population or Process Means with Independent Samples / Comparing More Than Two Treatments with Samples Selected in Blocks / Analysis of Variance: A Comprehensive Example / Summary / Appendix 8: Computer Instructions for Using MINITAB, Excel, and JMP IN 9. SIMPLE LINEAR REGRESSION ANALYSIS Bridging to New Topics / Relationships Between Two Variables: The Simple Linear Regression Model / Estimating the Parameters of the Simple Linear Regression Model / Statistical Inferences for the Simple Linear Regression Model / The Reliability of Estimates and Predictions / Factors That Affect Regression Standard Errors: Some Design Considerations / Correlation: Measuring the Linear Association Between Y and X / Simple Linear Regression: A Comprehensive Example / Summary / Appendix 9A: Computer Instructions for Using MINITAB, Excel, and JMP IN / Appendix 9B: Determining Least Squares Estimates Using a Calculator 10. MULTIPLE LINEAR REGRESSION Bridging to New Topics / The Multiple Linear Regression Model / Estimating the Parameters of the Multiple Linear Regression Model / How Good Is the Model? / Statistical Inference for Multiple Linear Regression / Incorporating Qualitative Variables in Multiple Linear Regression: Dummy Variables / Curvilinear Regression Models / Detecting Model Deficiencies and Avoiding Pitfalls: Residual Analysis and Collinearity / Criteria for Selecting the Best Set of Predictor Variables / Multiple Linear Regression: A Comprehensive Example / Summary / Appendix 10: Computer Instructions for Using MINITAB, Excel, and JMP IN 11. GOODNESS-OF-FIT PROCEDURES AND CONTINGENCY TABLES Bridging to New Topics / The Chi-Square Goodness-of-Fit Procedure / Analysis of Two-Way Contingency Tables: The Chi-Square Procedure for Independence / Summary / Appendix 11: Computer Instructions for Using MINITAB, Excel, and JMP IN 12. TIME SERIES ANALYSIS AND FORECASTING Bridging to New Topics / Time Series Patterns / Forecasting with Exponential Smoothing / Forecasting with Regression Models / Summary / Appendix 12: Computer Instructions for Using MINITAB, Excel, and JMP IN 13. METHODS FOR PROCESS IMPROVEMENT AND STATISTICAL QUALITY CONTROL Bridging to New Topics / Process Improvement Strategies / Statistical Control Charts / Control Charts for the Average and Variation of Process Outputs: X [overbar] and S charts / Control Charts for Process Proportions: p Charts / Summary / Appendix 13: Computer Instructions for Using MINITAB, Excel, and JMP IN / APPENDIX: STATISTICAL TABLES / ANSWERS TO SELECTED ODD-NUMBERED EXERCISES / INDEX