# 4.2 DQ response 2

Statistical Tests
Alyssa Ridao posted May 27, 2020 4:22 PM
Week 4 Discussion 1

Statistical Tests

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Dr. Ruth Obregon

May 27, 2020

Alyssa Ridao

The Oxford dictionary defines statistics as the practice or science of collecting and analyzing numerical data in large quantities, especially for the purpose of inferring proportions in a whole from those in a representative sample. Statistics can range from birth and death rate, infection rate, football goal average and so on. As evidence-based practice flourishes, it is a requirement that its current literature be critically appraised. In order to do this, nurses need a fundamental understanding of statistical analysis to translate the results of empirical nursing research into nursing practice. The common types of statistical techniques in nursing research are those that measure differences in groups like independent samples t-test, paired sample t-tests, and analysis of variance and those that measure relationships like the Pearson product moment correlation and chi-square.(Gravetter & Wallnau, 2012)

According to Main and Ogaz (2016), “The statistical analysis of research includes both descriptive and inferential statistics. Descriptive statistics are used to summarize and organize data including measures of central tendency and measures of variability. Inferential statistics are utilized to infer results on target populations from a sample population” (p.5). My chosen statistical technique is paired sample t-test wherein the researcher compares two sets of information from one group of people on a continuous dependent variable; this is utilized mostly for pre and post intervention studies.(Cumming, 2012) An example of this would be comparing if there is a change in patient’s knowledge after a diabetic lifestyle teaching intervention. I would use pre and posttest questionnaires as level of measurements then gather data from the exam to compare if there is a change in the scores which will indicate clinical significance of my study.

Reference:

Cumming, G. (2012). Understanding the new statistics effect sizes, confidence intervals, and meta-analysis. New York, NY: Routledge.

Gravetter, F. J. & Wallnau, L. B. (2012). Statistics for the behavioral health sciences (9th ed). Belmont, CA: Wadsworth.

Main, Maria E. and Ogaz, Veletta L. (2016) “Common Statistical Tests and Interpretation in Nursing Research, “International Journal of Faith Community Nursing: Vol. 2: Iss. 3, Article 2.

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