A brief introduction to probability and statistics / William Mendenhall, Robert J. Beaver, Barbara M. Beaver.

Accompanied by the text: Student solutions manual for Mendenhall, Beaver, and Beaver's Introduction to probability and statistics, by Barbara M. Beaver.

Introduction: An Invitation to Statistics -- The Population and the Sample -- Descriptive and Inferential Statistics -- Achieving the Objective of Inferential Statistics: The Necessary Steps -- 1. Describing Data with Graphs -- 1.1. Variables and Data -- 1.2. Types of Variables -- 1.3. Graphs for Categorical Data -- 1.4. Graphs for Quantitative Data -- 1.5. Relative Frequency Histograms -- About Minitab -- Introduction to Minitab -- Case Study How Is Your Blood Pressure? -- 2. Describing Data with Numerical Measures -- 2.1. Describing a Set of Data with Numerical Measures -- 2.2. Measures of Center -- 2.3. Measures of Variability -- 2.4. On the Practical Significance of the Standard Deviation -- 2.5. A Check on the Calculation of s -- 2.6. Measures of Relative Standing -- 2.7. The Box Plot -- About Minitab -- Numerical Descriptive Measures -- Case Study The Boys of Summer -- 3. Describing Bivariate Data -- 3.1. Bivariate Data -- 3.2. Graphs for Qualitative Variables -- 3.3. Scatterplots for Two Quantitative Variables -- 3.4. Numerical Measures for Quantitative Bivariate Data -- About Minitab -- Describing Bivariate Data -- Case Study Do You Think Your Dishes Are Really Clean? -- 4. Probability and Probability Distributions -- 4.1. The Role of Probability in Statistics -- 4.2. Events and the Sample Space -- 4.3. Calculating Probabilities Using Simple Events -- 4.4. Useful Counting Rules (Optional) -- 4.5. Event Composition and Event Relations -- 4.6. Conditional Probability and Independence -- 4.7. Bayes' Rule (Optional) -- 4.8. Discrete Random Variables and Their Probability Distributions -- About Minitab -- Discrete Probability Distributions -- Case Study Probability and Decision Making in the Congo -- 5. Several Useful Discrete Distributions -- 5.1. Introduction -- 5.2. The Binomial Probability Distribution -- 5.3. The Poisson Probability Distribution -- 5.4. The Hypergeometric Probability Distribution -- About Minitab -- Binomial and Poisson Probabilities -- Case Study A Mystery: Cancers Near a Reactor -- 6. The Normal Probability Distribution -- 6.1. Probability Distributions for Continuous Random Variables -- 6.2. The Normal Probability Distribution -- 6.3. Tabulated Areas of the Normal Probability Distribution -- 6.4. The Normal Approximation to the Binomial Probability Distribution (Optional) -- About Minitab -- Normal Probabilities -- Case Study The Long and the Short of It -- 7. Sampling Distributions -- 7.1. Introduction -- 7.2. Sampling Plans and Experimental Designs -- 7.3. Statistics and Sampling Distributions -- 7.4. The Central Limit Theorem -- 7.5. The Sampling Distribution of the Sample Mean -- 7.6. The Sampling Distribution of the Sample Proportion -- 7.7. A Sampling Application: Statistical Process Control (Optional) -- About Minitab -- The Central Limit Theorem at Work -- Case Study Sampling the Roulette at Monte Carlo -- 8. Large-Sample Estimation -- 8.1. Where We've Been -- 8.2. Where We're Going -- Statistical Inference -- 8.3. Types of Estimators -- 8.4. Point Estimation -- 8.5. Interval Estimation -- 8.6. Estimating the Difference Between Two Population Means -- 8.7. Estimating the Difference Between Two Binomial Proportions -- 8.8. One-Sided Confidence Bounds -- 8.9. Choosing the Sample Size -- Case Study How Reliable Is That Poll? -- 9. Large-Sample Tests of Hypotheses -- 9.1. Testing Hypotheses about Population Parameters -- 9.2. A Statistical Test of Hypothesis -- 9.3. A Large-Sample Test about a Population Mean -- 9.4. A Large-Sample Test of Hypothesis for the Difference between Two Population Means -- 9.5. A Large-Sample Test of Hypothesis for a Binomial Proportion -- 9.6. A Large-Sample Test of Hypothesis for the Difference between Two Binomial Proportions -- 9.7. Some Comments on Testing Hypotheses -- Case Study An Aspirin a Day.? -- 10. Inference from Small Samples -- 10.1. Introduction -- 10.2. Student's t Distribution -- 10.3. Small-Sample Inferences Concerning a Population Mean -- 10.4. Small-Sample Inferences for the Difference between Two Population Means: Independent Random Samples -- 10.5. Small-Sample Inferences for the Difference between Two Means: A Paired-Difference Test -- 10.6. Inferences Concerning a Population Variance -- 10.7. Comparing Two Population Variances -- 10.8. Revisiting the Small-Sample Assumptions -- About Minitab -- Small-Sample Testing and Estimation -- Case Study How Would You Like a Four-Day Work Week? -- 11. The Analysis of Variance -- 11.1. The Design of an Experiment -- 11.2. What Is an Analysis of Variance? -- 11.3. The Assumptions for an Analysis of Variance -- 11.4. The Completely Randomized Design: A One-Way Classification -- 11.5. The Analysis of Variance for a Completely Randomized Design -- 11.6. Ranking Population Means -- 11.7. Revisiting the Analysis of Variance Assumptions -- 11.8. A Brief Summary -- About Minitab -- Analysis of Variance Procedures -- Case Study "Are You at Risk?" -- 12. Linear Regression and Correlation -- 12.1. Introduction -- 12.2. A Simple Linear Probabilistic Model -- 12.3. The Method of Least Squares -- 12.4. An Analysis of Variance for Linear Regression -- 12.5. Testing the Usefulness of the Linear Regression Model -- 12.6. Estimation and Prediction Using the Fitted Line -- 12.7. Revisiting the Regression Assumptions -- 12.8. Correlation Analysis -- About Minitab -- Linear Regression Procedures -- Case Study Is Your Car "Made in the U.S.A."? -- 13. Analysis of Categorical Data -- 13.1. A Description of the Experiment -- 13.2. Pearson's Chi-Square Statistic -- 13.3. Testing Specified Cell Probabilities: The Goodness-of-Fit Test -- 13.4. Contingency Tables: A Two-Way Classification -- 13.5. Comparing Several Multinomial Populations: A Two-Way Classification with Fixed Row or Column Totals -- 13.6. The Equivalence of Statistical Tests -- 13.7. Other Applications of the Chi-Square Test -- About Minitab -- The Chi-Square Test -- Case Study Can a Marketing Approach Improve Library Services? -- Appendix I. Tables -- Table 1. Cumulative Binomial Probabilities -- Table 2. Cumulative Poisson Probabilities -- Table 3. Normal Curve Areas -- Table 4. Critical Values of t -- Table 5. Critical Values of Chi-Square -- Table 6. Percentage Points of the F Distribution -- Table 7. Random Numbers -- Table 8. Percentage Points of the Studentized Range, q(k, df) -- Answers to Selected Exercises -- Index.

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