This introductory textbook explores the role of research in health care and focuses in particular on the importance of organizing and describing research data using basic statistics. The goal of the text is to teach students how to analyze data and present the results of evidence-based data analysis. Based on the commonly-used SPSS software, a comprehensive range of statistical techniques-both parametric and non-parametric-are presented and explained. Examples are given from nursing, health administration, and health professions, followed by an opportunity for students to immediately practice the technique.
This introductory textbook explores the role of research in health care and focuses in particular on the importance of organizing and describing research data using basic statistics. The goal of the text is to teach students how to analyze data and present the results of evidence-based data analysis. Based on the commonly-used SPSS software, a comprehensive range of statistical techniques-both parametric and non-parametric-are presented and explained. Examples are given from nursing, health administration, and health professions, followed by an opportunity for students to immediately practice the technique.
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Produkt-Hinweis
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Höhe: 229 mm
Breite: 178 mm
Dicke: 15 mm
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ISBN-13
978-0-7817-5459-0 (9780781754590)
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Schweitzer Klassifikation
Chapter One: Using Research and Statistics In Health Care Chapter Two: Descriptive Statistics: Getting to Know the Data Chapter Three: Building Blocks for Using Inferential Statistics Chapter Four: Inferential Statistics: Finding Relationships in the Data Chapter Five: The Independent T-test and the Mann-Whitney U-test: Comparing the Means Chapter Six: The Paired T-test and the Wilcoxon Matched-pairs Test: Comparing the Means of Two Related Groups Chapter Seven: The One-way ANOVA and the Kruskal-Wallis ANOVA: Comparing the Means of Three or More Unrelated Groups Chapter Eight: The Repeated-measures ANOVA and the Friedman's ANOVA by Rank: Comparing the Means of Three or More Related Groups Chapter Nine: The Pearson and the Spearman Correlation Coefficients: Measuring the Association of Two Variables Chapter Ten: The Chi-square Statistic and the McNemar Test: Examining Relationships between Categorical Variables Chapter Eleven: Model Building with Linear and Logistic Regression Chapter Twelve: Writing for Publication Appendix A Percent of Total Area of Normal Curve Between a z-Score and the Meam Appendix B Critical Values of the Student t-Statistic Appendix C Critical Values of "U" for the Mann-Whitney U-Test Appendix D Critical Values of "T," the Wilcoxon Signed-Rank Statistic 391 Appendix E Critical Values of "F" for Testing ANOVA Models Appendix F Critical Values of "H" for the Kruskal-Wallis ANOVA by Rank Appendix G Critical Values of Dunn's Q for Nonparametric Multiple Comparison Testing Appendix H Exact Distribution of the Friedman's Xr 2 for the Friedman's ANOVA by Rank Comparing Three Related Groups Appendix I Significant Values of the Pearson Correlation Coefficient Appendix J Critical Values of the Spearman Correlation Coefficient Appendix K Significant Values of the Chi-Square Statistic Glossary Index
