23 Jul Quantitative Analysis and Interpretation: t-Test and ANOVA

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Week 5: Quantitative Analysis and Interpretation: t-Test and ANOVA

Statistics provide a variety of information that can shape healthcare. Statistics can indicate disparity in care, effectiveness of treatments plans, and predict future outcomes. As a future DNP-prepared nurse, understanding how to analyze and interpret statistics will provide you the opportunity to utilize research in directing patient care and implementing procedures to ultimately improve patient success.

When comparing patients, treatment methods, or healthcare practices, it will be important to consider differences amongst groups. Statistics give us the opportunity to explore and determine these differences to properly analyze the data, make recommendations, or determine treatment options. As a DNP-prepared nurse, using statistics to determine differences may assist you in making the best decisions for your patients and practice.

This week, you will examine the use of inferential statistics in research. You will also consider the strengths and weaknesses of using both t-tests and ANOVA.

Learning Objectives

Students will:

Analyze the use of t-tests, ANOVA, and inferential statistics in research and evidence-based practice

Evaluate strengths and weaknesses of inferential statistics in supporting evidence-based practice

Interpret results and output from t-tests and ANOVA

Summarize ANOVA Statistics

Assignment: t-Tests and ANOVA

You are a DNP-Prepared nurse tasked with evaluating patient care at your practice compared to patient care at affiliated practices. You have noticed that a key complaint from your patients concerns the wait times associated with each patient visit. Based on these complaints, you have decided to compare the wait times at your practice to the wait times at affiliated practices. After recording the wait times at each practice, for 50 individual patients at each practice, you are now prepared to analyze your data. What approach will you use to analyze the data?

Photo Credit: Dave and Les Jacobs / Blend Images / Getty Images

In the scenario provided, you might decide to use, the Analysis of Variance (ANOVA) approach. “ANOVA is a statistical procedure that compares data between two or more groups or conditions to investigate the presence of differences between those groups on some continuous dependent variable” (Gray & Grove, 2020). ANOVA is often a recommended statistical technique, as it has low chance of error for determining differences between three or more groups.

For this Assignment, analyze the ANOVA statistics provided in the ANOVA Exercises SPSS Output document. Examine the results to determine the differences and reflect on how you would interpret these results.

Reference: Gray, J. R., & Grove, S. K. (2020). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (9th ed.). Elsevier.

To Prepare:

Review the Week 5 ANOVA Exercises SPSS Output provided in this week’s Learning Resources.

Review the Learning Resources on how to interpret ANOVA results to determine differences.

Consider the results presented in the SPSS output and reflect on how you might interpret the results presented.

The Assignment: (2–3 pages)

Summarize your interpretation of the ANOVA statistics provided in the Week 5 ANOVA Exercises SPSS Output document.

Note: Interpretation of the ANOVA output should include identification of the p-value to determine whether the differences between the group means are statistically significant.

Be sure to accurately evaluate each of the results presented (descriptives, ANOVA results, and multiple comparisons using post-hoc analysis)

Reminder: The College of Nursing requires that all papers submitted include a title page, introduction, summary, and references. The Sample Paper provided at the Walden Writing Center provides an example of those required elements (available at https://academicguides.waldenu.edu/writingcenter/templates/general#s-lg-box-20293632). All papers submitted must use this formatting.