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Learn how to expand your interpretation and application of statistical methods used in nursing and health sciences research articles with Statistics for Nursing Research: A Workb… Read more
AI & BIG DATA
Save up to 25% on AI & Big Data books, eBooks & Journals
Learn how to expand your interpretation and application of statistical methods used in nursing and health sciences research articles with Statistics for Nursing Research: A Workbook for Evidence-Based Practice, 3rd Edition. Perfect for those seeking to more effectively build an evidence-based practice, this collection of practical exercises guides you in how to critically appraise sampling and measurement techniques, evaluate results, and conduct a power analysis for a study. Written by nursing research and statistics experts Drs. Susan K. Grove and Daisha Cipher, this is the only statistics workbook for nurses to include research examples from both nursing and the broader health sciences literature. This new third edition features new research article excerpts and examples, an enhanced focused on statistical methods commonly used in DNP projects, new examples from quality improvement projects, new content on paired samples analysis, expanded coverage of calculating descriptive statistics, an online Research Article Library, and more! Whether used in undergraduate, master’s, or doctoral education or in clinical practice, this workbook is an indispensable resource for any nursing student or practicing nurse needing to interpret or apply statistical data.
Part 1: Understanding Statistical Methods
1. Identifying Levels of Measurement: Nominal, Ordinal, Interval, and Ratio
2. Identifying Probability and Nonprobability Sampling Methods in Studies
3. Understanding the Sampling Section of a Research Report: Population, Sampling Criteria, Sample Size, Refusal Rate, and Attrition Rate
4. Understanding Reliability of Measurement Methods
5. Understanding Validity of Measurement Methods
6. Understanding Frequencies and Percentages
7. Interpreting Line Graphs
8. Measures of Central Tendency: Mean, Median, and Mode
9. Measures of Dispersion: Range and Standard Deviation
10. Description of a Study Sample
11. Interpreting Scatterplots
12. Algorithm for Determining the Appropriateness of Inferential Statistical Techniques
13. Understanding Pearson Product-Moment Correlation Coefficient
14. Understanding Simple Linear Regression
15. Understanding Multiple Linear Regression
16. Understanding Independent Samples t-test
17. Understanding Paired or Dependent Samples t-test
18. Understanding Analysis of Variance (ANOVA) and Post Hoc Analyses
19. Understanding Pearson Chi Square
20. Understanding Spearman Rank-Order Correlation Coefficient
21. Understanding Mann-Whitney U Test
22. Understanding Wilcoxon Signed-Rank Test
Part 2: Conducting and Interpreting Statistical Analyses
23. Selecting Appropriate Analysis Techniques for Studies
24. Describing the Elements of Power Analysis: Power, Effect Size, Alpha, and Sample Size
25. Conducting Power Analysis
26. Determining the Normality of a Distribution
27. Calculating Descriptive Statistics
28. Calculating Pearson Product-Moment Correlation Coefficient
29. Calculating Simple Linear Regression
30. Calculating Multiple Linear Regression
31. Calculating t-tests for Independent Samples
32. Calculating t-tests for Paired (Dependent) Samples
33. Calculating Analysis of Variance (ANOVA) and Post Hoc Analyses Following ANOVA
34. Calculating Sensitivity and Specificity
35. Calculating Pearson Chi-Square
36. Calculating Odds Ratio and 95% Confidence Intervals
References
Appendices
Appendix A: Critical Values for Student's t Distribution
Appendix B: Critical Values of r for Pearson Product Moment Correlation Coefficient
Appendix C: Critical Values of F for α = 0.05 and α = 0.01
Appendix D: Critical Values of the χ2 Distribution
Index
SG
DC