Just the essentials of elementary statistics
著者
書誌事項
Just the essentials of elementary statistics
Brooks/Cole Pub. Co., c1999
2nd ed
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注記
Includes indexes
内容説明・目次
内容説明
Written by the author of the "Elementary Statistics", (7th ed) this brief paperback presents the core of elementary statistics in a language that is designed to speak to late-1990s students. The book focuses only on the essentials, allowing ready use in a variety of course structures, and promotes understanding and motivation by presenting statistics in a context that relates to personal experiences. It features modern ideas and an easy-to-comprehend exposition, and places consistent emphasis on real data and graphical analysis. Descriptive coverage of linear correlation and regression appears early.
目次
PART I: DESCRIPTIVE STATISTICS. 1. Statistics. What Is Statistics? Introduction to Basic Terms. Measurability and Variability. Data Collection. Comparison of Probability and Statistics. Statistics and the Computer. 2. Descriptive Analysis and Presentation of Single-Variable Data. Graphs, Pareto Diagrams, and Stem-and-Leaf Displays. Frequency Distributions and Histograms. Measures of Central Tendency. Measures of Dispersion. Mean and Standard Deviation of Frequency Distribution. Measures of Position. Intrepreting and Understanding Standard Deviation. The Art of Statistical Deception. 3. Descriptive Analysis and Presentation of Bivariate Data. Bivariate Data. Linear Correlation. Linear Regression. PART II: PROBABILITY. 4. Probability. The Nature of Probability. Probability of Events. Simple Sample Spaces. Rules of Probability. Mutually Exclusive Events and the Addition Rule. Independence, the Multiplication Rule, and Conditional Probability. Combining the Rules of Probability. 5. Probability Distributions (Discrete Variables). Random Variables. Probability Distributions of a Discrete Random Variable. Mean and Variance of a Discrete Probability Distribution. The Binomial Probability Distribution. Mean and Standard Deviation of the Binomial Distribution. 6. Normal Probability Distributions. Normal Probability Distributions. The Standard Normal Distribution. Applications of Normal Distributions. Notation. Normal Approximation of the Binomial. 7. Sample Variability. Sampling Distributions. The Central Limit Theorem. Application of the Central Limit Theorem. PART III: INFERENTIAL STATISTICS. 8. Introduction to Statistical Inferences. The Nature of Estimation. Estimation of Mean u (o known). The Nature of Hypothesis Testing. Hypothesis Test of Mean u (o known): A Probability-Value Approach. Hypothesis Test of Mean u (o known): A Classical Approach. 9. Inferences Involving One Population. Inferences About Mean u (o unknown). Inferences About the Binomial Probability of Success. 10. Inferences Involving Two Populations. Independent and Dependent Samples. Inferences Concerning the Mean Difference Using Two Dependent Samples. Inferences Concerning the Difference Between Means Using Two Independent Samples. Inferences Concerning the Difference Between Proportions Using Two Independent Samples. 11. Applications of Chi-Square. Chi-Square Statistic. Inferences Concerning Multinomial Experiments. Inferences Concerning Contingency Tables. APPENDIXES. Appendix A: Basic Principles of Counting. Appendix B: Tables. Answers to Selected Exercises. Answers to Practice Tests. Index of Minitab Commands. Formula Card.
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