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by Neil Weiss

Edition: 7TH 05Copyright: 2005

Publisher: Addison-Wesley Longman, Inc.

Published: 2005

International: No

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Introductory Statistics is the longer of the two texts (Elementary Statistics is the shorter one) and is appropriate for a one- or two-semester course. IS includes more detailed (but still flexible) coverage of probability and later coverage of Correlation and Regression. It also covers more advanced topics covered in the second semester course.

IS has a reputation for being thorough and precise, and for using real data extensively. Students find the book readable and clear, and the math level is right for the diverse population that takes the introductory statistics course. The text thoroughly explains and illustrates concepts through an abundance of worked out examples.

1. The Nature of Statistics

2. Organizing Data

3. Descriptive Measures

4. Probability Concepts

5. Discrete Random Variables

6. The Normal Distribution

7. The Sampling Distribution of the Sample Mean

8. Confidence Intervals for One Population Mean

9. Hypothesis Tests for One Population Mean

10. Inferences for Two Population Means

11. Inferences for Population Standard Deviations

12. Inferences for Population Proportions

13. Chi-Square Procedures

14. Descriptive Methods in Regression and Correlation

15. Inferential Methods in Regression and Correlation

16. Analysis of Variance (ANOVA)

Module A: Multiple Regression Analysis (on CD)

Module B: Model Building in Regression (on CD)

Module C: Design of Experiments and Analysis of Variance (on CD)

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Summary

Introductory Statistics is the longer of the two texts (Elementary Statistics is the shorter one) and is appropriate for a one- or two-semester course. IS includes more detailed (but still flexible) coverage of probability and later coverage of Correlation and Regression. It also covers more advanced topics covered in the second semester course.

IS has a reputation for being thorough and precise, and for using real data extensively. Students find the book readable and clear, and the math level is right for the diverse population that takes the introductory statistics course. The text thoroughly explains and illustrates concepts through an abundance of worked out examples.

Table of Contents

1. The Nature of Statistics

2. Organizing Data

3. Descriptive Measures

4. Probability Concepts

5. Discrete Random Variables

6. The Normal Distribution

7. The Sampling Distribution of the Sample Mean

8. Confidence Intervals for One Population Mean

9. Hypothesis Tests for One Population Mean

10. Inferences for Two Population Means

11. Inferences for Population Standard Deviations

12. Inferences for Population Proportions

13. Chi-Square Procedures

14. Descriptive Methods in Regression and Correlation

15. Inferential Methods in Regression and Correlation

16. Analysis of Variance (ANOVA)

Module A: Multiple Regression Analysis (on CD)

Module B: Model Building in Regression (on CD)

Module C: Design of Experiments and Analysis of Variance (on CD)

Publisher Info

Publisher: Addison-Wesley Longman, Inc.

Published: 2005

International: No

Published: 2005

International: No

IS has a reputation for being thorough and precise, and for using real data extensively. Students find the book readable and clear, and the math level is right for the diverse population that takes the introductory statistics course. The text thoroughly explains and illustrates concepts through an abundance of worked out examples.

2. Organizing Data

3. Descriptive Measures

4. Probability Concepts

5. Discrete Random Variables

6. The Normal Distribution

7. The Sampling Distribution of the Sample Mean

8. Confidence Intervals for One Population Mean

9. Hypothesis Tests for One Population Mean

10. Inferences for Two Population Means

11. Inferences for Population Standard Deviations

12. Inferences for Population Proportions

13. Chi-Square Procedures

14. Descriptive Methods in Regression and Correlation

15. Inferential Methods in Regression and Correlation

16. Analysis of Variance (ANOVA)

Module A: Multiple Regression Analysis (on CD)

Module B: Model Building in Regression (on CD)

Module C: Design of Experiments and Analysis of Variance (on CD)