Statistics And Data Analysis For Nursing Research

Bol Partner

Statistics and Data Analysis for Nursing Research 2e Denise F. Polit, PdD Users praised the accessibility, clarity, and user-friendliness of the first edition of Statistics and Data Analysis for Nursing Research. Now, the push for evidence-based practice (EBP) in nursing and health care makes this new edition timely. The style and practical emphasis of the first edition have been retained, but important innovations have also been introduced, making it even easier to embark on a professional pathway that includes statistical analysis. As in the first edition, the content includes descriptive statistics, bivariate inferential statistics, and many widely-used multivariate statistics. It assumes virtually no prior knowledge of statistics. NEW TO THIS EDITION Emphasis on evidence-based practice · SPSS Version 16.0 was used to generate output for the book · Missing Values are demystified · Factor Analysis content is expanded · Power Analysis methods are explained Additional Resources: Online Applications Manual for Statistics and Data Analysis for Nursing Research 2e Online resource for Application Exercises with three complete data sets, compatible with SPSS, as well as additional resources. [Pearson Education] 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.

Bol

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.