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Introduction to Statistics Through Resampling Methods and R/S-PLUS(R)
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More About This Title Introduction to Statistics Through Resampling Methods and R/S-PLUS(R)

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PHILLIP I. GOOD, PHD, is Operations Manager of Information Research, a consulting firm specializing in statistical solutions for private and public organizations. He has published more than thirty scholarly works, more than 600 articles, and fourteen books, including Common Errors in Statistics (and How to Avoid Them) and A Manager's Guide to the Design and Conduct of Clinical Trials, both from Wiley.
  • English

English

Preface.

1. Variation.

1.1 Variation.

1.2. Collecting Data.

1.3. Summarizing Your Data.

1.4. Types of Data.

1.5. Reporting Your Results.

1.6. Measures of Location.

1.7. Samples and Populations.

1.8. Variation— Within and Between.

1.9. Summary and Review.

2. Probability.

2.1. Probability.

2.2. Binomial.

2.3. Condition Probability.

2.4. Independence.

2.5. Applications to Genetics.

2.6. Summary and Review.

3. Distributions.

3.1. Distribution of Values.

3.2. Discrete Distributions.

3.3. Continuous Distributions.

3.4. Properties of Independence Observations.

3.5. Testing A Hypothesis.

3.6. Estimating Effect Size.

3.7 Summary and Review.

4. Testing Hypotheses.

4.1. One-Sample Problems.

4.2. Comparing Two Samples.

4.3. Which Test Should e Use?

4.4. Summary and Review.

5. Designing an Experiment or Survey.

5.1. The Hawthorne Effect.

5.2. Designing an Experiment or Survey.

5.3. How Large a Sample.

5.4. Meta-Analysis.

5.5. Summary and Review.

6. Analyzing Complex Experiments.

6.1. Changes Measured in Percentages.

6.2. Comparing More Than Two Samples.

6.3. Equalizing Variances.

6.4. Categorical Data.

6.5. Multivariate Analysis.

6.6. Summary and Review.

7. Developing Models.

7.1. Models.

7.2. Regression.

7.3. Fitting a Regression Equation.

7.4. Problems with Regression.

7.5 Quantile Regression.

7.6. Validation.

7.7 Classification and Regression Trees.

7.8 Summary and Review.

8. Reporting Your Findings.

8.1. What to Report.

8.2. Text, Tables, of Graph?

8.3. Summarizing Your Results.

8.4 Reporting Analysis Results.

8.5 Exceptions are the Real Story.

9. Problem Solving.

9.1. Real Life Problems.

9.2. Problem Sets.

9.3. Solutions.

Appendix: S-PLUS.

Answers to Selected Exercises.

Subject Index.

Index to R Functions.

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English

"…easy to read and provides many interesting examples." (The American Statistician, November 2006)

"This is certainly one of the most impressive little paperback 200-page introductory statistics books that I will ever see…it would make a good nightstand book for every statistician." (Technometrics, May 2006)

"Good, a well-published statistical expert, is adept at introducing new ideas with well-structured scenarios, nicely illustrating his points, and presenting them in an effective, conversational tone." (CHOICE, January 2006)

"I would recommend this book to readers new to statistics, practitioners who lack the basics of statistical estimation and hypothesis, and students who need a side reference…" (MAA Reviews, January 3, 2006)

" … clearly written and ha(s) a very informal style that is pleasant to read, making the text accessible to the many." (Significance: Vol. 3, 2)

"…the books have plenty of wise advice for the application of statistics…" (Bulletin of Mathematical Biology ,2007)

‘…a very good introduction to statistics and focuses on the variety of problems which will be of interest to students in different disciplines.’ (Statistical Papers,48, 2007)

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