Module Five: Quantitative Studies – Data Analysis
Module 5 Overview
The method of data analysis in quantitative studies is always statistics of some type. Correlational studies use correlational statistics (t-tests, ANOVA, or chi-square are the most common). The research design helps to determine the type of statistics used to analyze the data. The most important part of the data analysis is the p value. Depending on the way the statistics were set up, a p value of <.05 or < .01 means the findings were statistically significant. Just because a finding is not statistically significant does not necessarily mean the results should be thrown out. Sometimes findings are not statistically significant, but are clinically significant. This is where the researcher’s judgment comes into play.
After completing this module, you will be able to:
Compare various statistical methods used in quantitative research
Reading & Resources
Read Chapters 16-20 In Polit, D.B., & Beck, C.T. (2016). Nursing research: Generating and assessing evidence for nursing research (10th ed). Philadelphia: Lippincott, Williams, & Wilkins.
Last modified: Thursday, September 6, 2018, 2:47 PM.
Choose a quantitative research article. How were the data analyzed in your research article? Now that you have reviewed the entire article, what other studies do you think need to be done in order to bring this solution into practice?
Remember to respond to at least two of your peers. Please refer to the Course Syllabus for the Participation Guidelines & Grading Rubric.