| Introduction: An Invitation to Statistics |
| The Population and the Sample |
| Descriptive and Inferential Statistics |
| Achieving the Objective of Inferential Statistics: The Necessary Steps |
| Describing Data with Graphs / 1： |
| Variables and Data / 1.1： |
| Types of Variables / 1.2： |
| Graphs for Categorical Data / 1.3： |
| Graphs for Quantitative Data / 1.4： |
| Relative Frequency Histograms / 1.5： |
| Describing Data with Numerical Measures / 2： |
| Describing a Set of Data with Numerical Measures / 2.1： |
| Measures of Center / 2.2： |
| Measures of Variability / 2.3： |
| On the Practical Significance of the Standard Deviation / 2.4： |
| A Check on the Calculation of s / 2.5： |
| Measures of Relative Standing / 2.6： |
| The Five-Number Summary and the Box Plot / 2.7： |
| Describing Bivariate Data / 3： |
| Bivariate Data / 3.1： |
| Graphs for Qualitative Variables / 3.2： |
| Scatterplots for Two Quantitative Variables / 3.3： |
| Numerical Measures for Quantitative Bivariate Data / 3.4： |
| Probability and Probability Distributions / 4： |
| The Role of Probability in Statistics / 4.1： |
| Events and the Sample Space / 4.2： |
| Calculating Probabilities Using Simple Events / 4.3： |
| Useful Counting Rules (Optional) / 4.4： |
| Event Relations and Probability Rules / 4.5： |
| Conditional Probability, Independence, and the Multiplicative Rule / 4.6： |
| Bayes' Rule (Optional) / 4.7： |
| Discrete Random Variables and Their Probability Distributions / 4.8： |
| Several Useful Discrete Distributions / 5： |
| Introduction / 5.1： |
| The Binomial Probability Distribution / 5.2： |
| The Poisson Probability Distribution / 5.3： |
| The Hypergeometric Probability Distribution / 5.4： |
| The Normal Probability Distribution / 6： |
| Probability Distributions for Continuous Random Variables / 6.1： |
| Tabulated Areas of the Normal Probability Distribution / 6.2： |
| The Normal Approximation to the Binomial Probability Distribution (Optional) / 6.4： |
| Sampling Distributions / 7： |
| Sampling Plans and Experimental Designs / 7.1： |
| Statistics and Sampling Distributions / 7.3： |
| The Central Limit Theorem / 7.4： |
| The Sampling Distribution of the Sample Mean / 7.5： |
| The Sampling Distribution of the Sample Proportion / 7.6： |
| A Sampling Application: Statistical Process Control (Optional) / 7.7： |
| Large-Sample Estimation / 8： |
| Where We've Been / 8.1： |
| Where We're Going--Statistical Inference / 8.2： |
| Types of Estimators / 8.3： |
| Point Estimation / 8.4： |
| Interval Estimation / 8.5： |
| Estimating the Difference between Two Population Means / 8.6： |
| Estimating the Difference between Two Binomial Proportions / 8.7： |
| One-Sided Confidence Bounds / 8.8： |
| Choosing the Sample Size / 8.9： |
| Large-Sample Tests of Hypotheses / 9： |
| Testing Hypotheses about Population Parameters / 9.1： |
| A Statistical Test of Hypothesis / 9.2： |
| A Large-Sample Test about a Population Mean / 9.3： |
| A Large-Sample Test of Hypothesis for the Difference between Two Population Means / 9.4： |
| A Large-Sample Test of Hypothesis for a Binomial Proportion / 9.5： |
| A Large-Sample Test of Hypothesis for the Difference between Two Binomial Proportions / 9.6： |
| Some Comments on Testing Hypotheses / 9.7： |
| Inference from Small Samples / 10： |
| Student's t Distribution / 10.1： |
| Small-Sample Inferences Concerning a Population Mean / 10.3： |
| Small-Sample Inferences for the Difference between Two Population Means: Independent Random Samples / 10.4： |
| Small-Sample Inferences for the Difference between Two Means: A Paired-Difference Test / 10.5： |
| Inferences Concerning a Population Variance / 10.6： |
| Comparing Two Population Variances / 10.7： |
| Revisiting the Small-Sample Assumptions / 10.8： |
| The Analysis of Variance / 11： |
| The Design of an Experiment / 11.1： |
| What Is an Analysis of Variance? / 11.2： |
| The Assumptions for an Analysis of Variance / 11.3： |
| The Completely Randomized Design: A One-Way Classification / 11.4： |
| The Analysis of Variance for a Completely Randomized Design / 11.5： |
| Ranking Population Means / 11.6： |
| The Randomized Block Design: A Two-Way Classification / 11.7： |
| The Analysis of Variance for a Randomized Block Design / 11.8： |
| The a x b Factorial Experiment: A Two-Way Classification / 11.9： |
| The Analysis of Variance for an a x b Factorial Experiment / 11.10： |
| Revisiting the Analysis of Variance Assumptions / 11.11： |
| A Brief Summary / 11.12： |
| Linear Regression and Correlation / 12： |
| A Simple Linear Probabilistic Model / 12.1： |
| The Method of Least Squares / 12.3： |
| An Analysis of Variance for Linear Regression / 12.4： |
| Testing the Usefulness of the Linear Regression Model / 12.5： |
| Diagnostic Tools for Checking the Regression Assumptions / 12.6： |
| Estimation and Prediction Using the Fitted Line / 12.7： |
| Correlation Analysis / 12.8： |
| Multiple Regression Analysis / 13： |
| The Multiple Regression Model / 13.1： |
| A Multiple Regression Analysis / 13.3： |
| A Polynomial Regression Model / 13.4： |
| Using Quantitative and Qualitative Predictor Variables in a Regression Model / 13.5： |
| Testing Sets of Regression Coefficients / 13.6： |
| Interpreting Residual Plots / 13.7： |
| Stepwise Regression Analysis / 13.8： |
| Misinterpreting a Regression Analysis / 13.9： |
| Steps to Follow When Building a Multiple Regression Model / 13.10： |
| Analysis of Categorical Data / 14： |
| A Description of the Experiment / 14.1： |
| Pearson's Chi-Square Statistic / 14.2： |
| Testing Specified Cell Probabilities: The Goodness-of-Fit Test / 14.3： |
| Contingency Tables: A Two-Way Classification / 14.4： |
| Comparing Several Multinomial Populations: A Two-Way Classification with Fixed Row or Column Totals / 14.5： |
| The Equivalence of Statistical Tests / 14.6： |
| Other Applications of the Chi-Square Test / 14.7： |
| Nonparametric Statistics / 15： |
| The Wilcoxon Rank Sum Test: Independent Random Samples / 15.1： |
| The Sign Test for a Paired Experiment / 15.3： |
| A Comparison of Statistical Tests / 15.4： |
| The Wilcoxon Signed-Rank Test for a Paired Experiment / 15.5： |
| The Kruskal-Wallis H Test for Completely Randomized Designs / 15.6： |
| The Friedman F[subscript r] Test for Randomized Block Designs / 15.7： |
| Rank Correlation Coefficient / 15.8： |
| Summary / 15.9： |
| Appendix I |
| Cumulative Binomial Probabilities / Table 1： |
| Cumulative Poisson Probabilities / Table 2： |
| Areas under the Normal Curve / Table 3： |
| Critical Values of t / Table 4： |
| Critical Values of Chi-Square / Table 5： |
| Percentage Points of the F Distribution / Table 6： |
| Critical Values of T for the Wilcoxon Rank Sum Test, n[subscript 1] [less than or equal] n[subscript 2] / Table 7： |
| Critical Values of T for the Wilcoxon Signed-Rank Test, n = 5(1)50 / Table 8： |
| Critical Values of Spearman's Rank Correlation Coefficient for a One-Tailed Test / Table 9： |
| Random Numbers / Table 10： |
| Percentage Points of the Studentized Range, q[subscript [alpha](k, df) / Table 11： |
| Answers to Selected Exercises |
| Index |
| Credits |
| Introduction: An Invitation to Statistics |
| The Population and the Sample |
| Descriptive and Inferential Statistics |
図書
