Applied Statistics: Analysis of Variance and Regression / Edition 3

Hardcover (Print)
Used and New from Other Sellers
Used and New from Other Sellers
from $87.95
Usually ships in 1-2 business days
(Save 47%)
Other sellers (Hardcover)
  • All (10) from $87.95   
  • New (5) from $126.39   
  • Used (5) from $87.95   

Overview

The Wiley Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.

". . . overall this is an excellent book . . . I recommend this book to everyone . . ."
Statistical Methods in Medical Research

". . . it contains a wealth of useful up-to-date information and examples from the health sciences."
Technometrics

Applied Statistics: Analysis of Variance and Regression, Third Edition has been thoroughly revised to provide a comprehensive and up-to-date combination of sound statistical methodology, practical advice on the application of this methodology, and interpretation of output from statistical programs. Special features include comprehensive treatment of each topic, from summarization of data to presentation of results; a greater emphasis on regression, data screening, and confidence intervals; in-depth discussion of design-related topics such as mixed models and random effects; and overviews of more advanced topics. This valuable, self-contained textbook is eminently suitable for upper-undergraduate/graduate students and applied researchers with an interest in ANOVA techniques.

Read More Show Less

Editorial Reviews

From the Publisher
"…beginning level graduate students in statistics will find this book very valuable." (Journal of Statistical Computation and Simulation, January 2006)

"…Overall this is an excellent book…I recommend this book to everyone…" (Statistical Methods in Medical Research, Vol. 14, 2005)

"…The book is an excellent material for describing the data as well as a useful textbook for students to understand, apply and to interpret the statistical methods." (Zentralbaltt MATH, May 2005)

"…it contains a wealth of useful up-to-date information and examples from the health sciences." (Technometrics, November 2004)

"The level of the book is also more consistently intermediate...a few more advanced topics are now excluded." (The American Statistician, August 2004)

Read More Show Less

Product Details

Meet the Author

RUTH M. MICKEY, PHD, is Professor of Statistics at the University of Vermont in Burlington.

OLIVE JEAN DUNN, PHD, is Professor Emeritus at the University of California, Los Angeles.

VIRGINIA A. CLARK, PHD, is also Professor Emeritus at the University of California, Los Angeles. Drs. Dunn and Clark are the authors of Basic Statistics: A Primer for Biomedical Sciences, Third Edition, published by Wiley.

Read More Show Less

Table of Contents

Preface.

1. Data Screening.

1.1 Variables and Their Classification.

1.2 Describing the Data.

1.3 Departures from Assumptions.

1.4 Summary.

2. One-Way Analysis of Variance Design.

2.1 One-Way Analysis of Variance with Fixed Effects.

2.2 One-Way Analysis of Variance with Random Effects.

2.3 Designing an Observational Study or Experiment.

2.4 Checking if the Data Fit the One-Way ANOVA Model.

2.5 What to Do if the Data Do Not Fit the Model.

2.6 Presentation and Interpretation of Results.

2.7 Summary.

3. Estimation and Simultaneous Inference.

3.1 Estimation for Single Population Means.

3.2 Estimation for Linear Combinations of Population Means.

3.3 Simultaneous Statistical Inference.

3.4 Inference for Variance Components.

3.5 Presentation and Interpretation of Results.

3.6 Summary.

4. Hierarchical or Nested Design.

4.1 Example.

4.2 The Model.

4.3 Analysis of Variance Table and F Tests.

4.4 Estimation of Parameters.

4.5 Inferences with Unequal Sample Sizes.

4.6 Checking If the Data Fit the Model.

4.7 What to Do If the Data Don't Fit the Model.

4.8 Designing a Study.

4.9 Summary.

5. Two Crossed Factors: Fixed Effects and Equal Sample Sizes.

5.1 Example.

5.2 The Model.

5.3 Interpretation of Models and Interaction.

5.4 Analysis of Variance and F Tests.

5.5 Estimates of Parameters and Confidence Intervals.

5.6 Designing a Study.

5.7 Presentation and Interpretation of Results.

5.8 Summary.

6 Randomized Complete Block Design.

6.1 Example.

6.2 The Randomized Complete Block Design.

6.3 The Model.

6.4 Analysis of Variance Table and F Tests.

6.5 Estimation of Parameters and Confidence Intervals.

6.6 Checking If the Data Fit the Model.

6.7 What to Do if the Data Don't Fit the Model.

6.8 Designing a Randomized Complete Block Study.

6.9 Model Extensions.

6.10 Summary.

7. Two Crossed Factors: Fixed Effects and Unequal Sample Sizes.

7.1 Example.

7.2 The Model.

7.3 Analysis of Variance and F Tests.

7.4 Estimation of Parameters and Confidence Intervals.

7.5 Checking If the Data Fit the Two-Way Model.

7.6 What To Do If the Data Don't Fit the Model.

7.7 Summary.

8. Crossed Factors: Mixed Models.

8.1 Example.

8.2 The Mixed Model.

8.3 Estimation of Fixed Effects.

8.4 Analysis of Variance.

8.5 Estimation of Variance Components.

8.6 Hypothesis Testing.

8.7 Confidence Intervals for Means and Variance Components.

8.8 Comments on Available Software.

8.9 Extensions of the Mixed Model.

8.10 Summary.

9. Repeated Measures Designs.

9.1 Repeated Measures for a Single Population.

9.2 Repeated Measures with Several Populations.

9.3 Checking if the Data Fit the Repeated Measures Model.

9.4 What to Do if the Data Don't Fit the Model.

9.5 General Comments on Repeated Measures Analyses.

9.6 Summary.

10. Linear Regression: Fixed X Model.

10.1 Example.

10.2 Fitting a Straight Line.

10.3 The Fixed X Model.

10.4 Estimation of Model Parameters and Standard Errors.

10.5 Inferences for Model Parameters: Confidence Intervals.

10.6 Inference for Model Parameters: Hypothesis Testing.

10.7 Checking if the Data Fit the Regression Model.

10.8 What to Do if the Data Don't Fit the Model.

10.9 Practical Issues in Designing a Regression Study.

10.10 Comparison with One-Way ANOVA.

10.11 Summary.

11. Linear Regression: Random X Model and Correlation.

11.1 Example.

11.2 Summarizing the Relationship Between X and Y.

11.3 Inferences for the Regression of Y and X.

11.4 The Bivariate Normal Model.

11.5 Checking if the Data Fit the Random X Regression Model.

11.6 What to Do if the Data Don't Fit the Random X Model.

11.7 Summary.

12. Multiple Regression.

12.1 Example.

12.2 The Sample Regression Plane.

12.3 The Multiple Regression Model.

12.4 Parameters Standard Errors, and Confidence Intervals.

12.5 Hypothesis Testing.

12.6 Checking If the Data Fit the Multiple Regression Model.

12.7 What to Do If the Data Don't Fit the Model.

12.8 Summary.

13. Multiple and Partial Correlation.

13.1 Example.

13.2 The Sample Multiple Correlation Coefficient.

13.3 The Sample Partial Correlation Coefficient.

13.4 The Joint Distribution Model.

13.5 Inferences for the Multiple Correlation Coefficient.

13.6 Inferences for Partial Correlation Coefficients.

13.7 Checking If the Data Fit the Joint Normal Model.

13.8 What to Do If the Data Don't Fit the Model.

13.9 Summary.

14. Miscellaneous Topics in Regression.

14.1 Models with Dummy Variables.

14.2 Models with Interaction Terms.

14.3 Models with Polynomial Terms.

14.4 Variable Selection.

14.5 Summary.

15. Analysis of Covariance.

15.1 Example.

15.2 The ANCOVA Model.

15.3 Estimation of Model Parameters.

15.4 Hypothesis Tests.

15.5 Adjusted Means.

15.6 Checking If the Data Fit the ANCOVA Model.

15.7 What to Do if the Data Don't Fit the Model.

15.8 ANCOVA in Observational Studies.

15.9 What Makes a Good Covariate.

15.10 Measurement Error.

15.11 ANCOVA versus Other Methods of Adjustment.

15.12 Comments on Statistical Software.

15.13 Summary.

16. Summaries, Extensions, and Communication.

16.1 Summaries and Extensions of Models.

16.2 Communication of Statistics in the Context of Research Project.

Appendix A.

A.1 Expected Values and Parameters.

A.2 Linear Combinations of Variables and Their Parameters.

A.3 Balanced One-Way ANOVA, Expected Mean Squares.

A.4 Balanced One-Way ANOVA, Random Effects.

A.5 Balanced Nested Model.

A.6 Mixed Model.

A.7 Simple Linear Regression—Derivation of Least Squares Estimators.

A.8 Derivation of Variance Estimates from Simple Linear Regression.

Appendix B.

Index.

Read More Show Less

Customer Reviews

Be the first to write a review
( 0 )
Rating Distribution

5 Star

(0)

4 Star

(0)

3 Star

(0)

2 Star

(0)

1 Star

(0)

Your Rating:

Your Name: Create a Pen Name or

Barnes & Noble.com Review Rules

Our reader reviews allow you to share your comments on titles you liked, or didn't, with others. By submitting an online review, you are representing to Barnes & Noble.com that all information contained in your review is original and accurate in all respects, and that the submission of such content by you and the posting of such content by Barnes & Noble.com does not and will not violate the rights of any third party. Please follow the rules below to help ensure that your review can be posted.

Reviews by Our Customers Under the Age of 13

We highly value and respect everyone's opinion concerning the titles we offer. However, we cannot allow persons under the age of 13 to have accounts at BN.com or to post customer reviews. Please see our Terms of Use for more details.

What to exclude from your review:

Please do not write about reviews, commentary, or information posted on the product page. If you see any errors in the information on the product page, please send us an email.

Reviews should not contain any of the following:

  • - HTML tags, profanity, obscenities, vulgarities, or comments that defame anyone
  • - Time-sensitive information such as tour dates, signings, lectures, etc.
  • - Single-word reviews. Other people will read your review to discover why you liked or didn't like the title. Be descriptive.
  • - Comments focusing on the author or that may ruin the ending for others
  • - Phone numbers, addresses, URLs
  • - Pricing and availability information or alternative ordering information
  • - Advertisements or commercial solicitation

Reminder:

  • - By submitting a review, you grant to Barnes & Noble.com and its sublicensees the royalty-free, perpetual, irrevocable right and license to use the review in accordance with the Barnes & Noble.com Terms of Use.
  • - Barnes & Noble.com reserves the right not to post any review -- particularly those that do not follow the terms and conditions of these Rules. Barnes & Noble.com also reserves the right to remove any review at any time without notice.
  • - See Terms of Use for other conditions and disclaimers.
Search for Products You'd Like to Recommend

Recommend other products that relate to your review. Just search for them below and share!

Create a Pen Name

Your Pen Name is your unique identity on BN.com. It will appear on the reviews you write and other website activities. Your Pen Name cannot be edited, changed or deleted once submitted.

 
Your Pen Name can be any combination of alphanumeric characters (plus - and _), and must be at least two characters long.

Continue Anonymously

    If you find inappropriate content, please report it to Barnes & Noble
    Why is this product inappropriate?
    Comments (optional)