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. Students are guided through the complete analysis process from performing a statistical analysis to the rationale behind doing so. In addition, management of data, including how and why to recode variables for analysis, how to "clean" data, and how to work around missing data, is discussed.
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. Students are guided through the complete analysis process from performing a statistical analysis to the rationale behind doing so. In addition, management of data, including how and why to recode variables for analysis, how to "clean" data, and how to work around missing data, is discussed.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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
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
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