Statistics and Data Analysis for Nursing Research by Denise F. Polit

Statistics and Data Analysis for Nursing Research

byDenise F. Polit

Paperback | August 5, 2009

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The second edition of Statistics and Data Analysis for Nursing , uses a conversational style to teach students how to use statistical methods and procedures to analyze research findings. Readers are guided through the complete analysis process from performing a statistical analysis to the rationale behind doing so. Special focus is given to quantitative methods. Other features include management of data, how to "clean" data, and how to work around missing data. New to this edition are

updated research examples utilizinging examples from an international mix of studies published by nurse researchers in 2006-2009.  

About The Author

Susan Norwood is a professor of nursing at Saint Anselm College in Manchester, New Hampshire, where she teaches critical care nursing, professional nursing, ethics, and understanding suffering. She received her bachelor’s degree from the University of Massachusetts, Amherst, her master’s degree from Boston College, and her PhD from Uni...

Details & Specs

Title:Statistics and Data Analysis for Nursing ResearchFormat:PaperbackDimensions:490 pages, 9.9 × 8 × 0.7 inPublished:August 5, 2009Publisher:Pearson EducationLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0135085071

ISBN - 13:9780135085073

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Table of Contents

Chapter          Chapter Title

1                    Introduction to Data Analysis in an Evidence-Based Practice Environment

2                    Frequency Distribution: Tabulating and Displaying Data

3                    Central Tendency, Variability, and Location

4                    Correlation, Crosstabulation, and Risk Indexes: Describing Relationships:

5                    Statistical Inference

6                    t Tests

7                    Analysis of Variance

8                    Chi Square and Other Nonparametric Tests

9                    Correlation and Simple Regression

10                  Multiple Regression

11                  Analysis of Covariance, MANOVA, and Other Related Multivariate Techniques

12                  Using Logistic Regression

13                  Factor Analysis and Internal Consistency Reliability Analysis

14                  Missing Values

 

 

Appendix A: Theoretical Probability Tables

Appendix B: Power Analysis/Effect Size Tables

Appendix C: Tips on Handling Missing Data

Appendix D: Answers for Selected Exercises