Statistics and Data Analysis for Nursing Research / Edition 2

by Denise Polit

Overview

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.

Product Details

ISBN-13:	9780135085073
Publisher:	Pearson Education
Publication date:	08/05/2009
Edition description:	New Edition
Pages:	456
Product dimensions:	7.90(w) x 9.90(h) x 0.50(d)

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 Union Institute and University in Cincinnati, Ohio. She has been a practicing critical care nurse for over 30 years and a member of the American Association of Critical Care Nurses for nearly as long. She has published and presented in the areas of critical care nursing, nursing ethics, nursing history, suffering experienced by patients as well as health care providers, and conflict among members of the health care team.

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