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[null,"1.","Record Nr.",null,"UNINA9910153070403321"]
[null,null,"Autore",null,"Polit Denise F."]
[null,null,"Titolo",null,"Statistics and data analysis for nursing research / / Denise F. Polit"]
[null,null,"Pubbl/distr/stampa",null,"Harlow, England : , : Pearson, , [2014]"]
[{"$nulls":4},"Â©2014"]
[null,null,"ISBN",null,"1-292-05492-1"]
[null,null,"Edizione",null,"[Second edition, Pearson New International edition.]"]
[null,null,"Descrizione fisica",null,"1 online resource (445 pages) : illustrations, tables, graphs"]
[null,null,"Collana",null,"Always learning"]
[null,null,"Disciplina",null,"610.727"]
[null,null,"Soggetti",null,"Nursing - Research - Statistical methods"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Revised edition of: Data analysis & statistics for nursing research / Denise F. Polit. c1996."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Cover -- Table of Contents -- 1. Frequency Distributions: Tabulating and Displaying Data -- 2. Central Tendency, Variability, and Relative Standing -- 3. Bivariate Description: Crosstabulation, Risk Indexes, and Correlation -- 4. Statistical Inference -- 5. t Tests: Testing Two Mean Differences -- 6. Analysis of Variance -- 7. Chi-Square and Nonparametric Tests -- 8. Correlation and Simple Regression -- 9. Multiple Regression -- 10. Analysis of Covariance, Multivariate ANOVA, and Related Multivariate Analyses -- 11. Logistic Regression -- 12. Factor Analysis and Internal Consistency Reliability Analysis -- 13. Missing Values -- Appendix: Theoretical Sampling Distribution Tables -- Appendix: Tables for Power Analyses -- Index."]
[null,null,null,"Sommario/riassunto","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."]