Statistics and Data Analysis for Nursing

The second edition ofStatistics 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. Graduate nursing students or professional nurses needing an additional resource.

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.

Introduction to Data Analysis in an Evidence-Based Practice Environment	p. 1
Frequency Distributions: Tabulating and Displaying Data	p. 19
Central Tendency, Variability, and Relative Standing	p. 39
Bivariate Description: Crosstabulation, Risk Indexes, and Correlation	p. 59
Statistical Inference	p. 83
t Tests: Testing Two Mean Differences	p. 114
Analysis of Variance	p. 137
Chi-Square and Nonparametric Tests	p. 169
Correlation and Simple Regression	p. 197
Multiple Regression	p. 223
Analysis of Covariance, Multivariate ANOVA, and Related Multivariate Analyses	p. 263
Logistic Regression	p. 306
Factor Analysis and Internal Consistency Reliability Analysis	p. 333
Missing Values	p. 365
References	p. 392
Glossary	p. 397
Appendices
Theoretical Sampling Distribution Tables	p. 410
Tables for Power Analyses	p. 421
Answers to Exercises, Part A	p. 426
Index	p. 430
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Statistics and Data Analysis for Nursing Research

Summary

Author Biography

Table of Contents

Supplemental Materials