# NURS 8201 Week 5 Assignment t-Tests and ANOVA WALDEN

## 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

## Learning Resources

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.

• Chapter 25, “Using Statistics to Determine Differences” (pp. 687–698)

Donovan, L. M., & Payne, C. L. (2021). Organizational commitment of nurse faculty teaching in accelerated baccalaureate nursing programs. Nursing Education Perspectives42(2), 81–86. doi:10.1097/01.NEP.0000000000000764

Gray, J. A., & Kim, J. (2020). Palliative care needs of direct care workers caring for people with intellectual and developmental disabilities. British Journal of Learning Disabilities48(1), 69–77. doi:10.1111/bld.12318

Hilvert, E., Hoover, J., Sterling, A., & Schroeder, S. (2020). Comparing tense and agreement productivity in boys with fragile X syndrome, children with developmental language disorder, and children with typical development. Journal of Speech, Language and Hearing Research63(4), 1181–1194. doi:10.1044/2019_JSLHR-19-00022

Document: Week 5 ANOVA Exercises SPSS Output (PDF)

## Discussion: t-Tests and ANOVA in Clinical Practice

You are the DNP-prepared nurse responsible for overseeing staffing for the telehealth services provided at your practice. To determine the number of nurses that you might need for these services, you must determine how many patients might be interested in using the telehealth services versus the traditional clinical practice setting. For a week, you ask each patient visiting the practice his or her interest in setting up a visit via telehealth services. At the conclusion of the week, you use this data and reasoning to develop a statistic of the population interested in telehealth services. You have successfully used inferential statistics to help guide your decision-making for your practice.

Photo Credit: fizkes / Adobe Stock

The scenario outlined provides a random sampling and assumptions to develop a conclusion. With assumptions, and in this case, a small random sampling, this scenario is ripe with the possibility of error. However, how might inferential statistics be used in a valid and credible way?

The design of a study determines the validity of the results, and if done following appropriate techniques, inferential statistics can determine clear differences and help researchers to form conclusions. In your Discussion, you will focus on two forms of identifying differences in groups: t-tests and analysis of variance (ANOVA).

For this Discussion, review the Learning Resources and reflect on a healthcare issue of interest to find a research article in which to analyze the use of inferential statistical analysis. Reflect on how the study was comprised, the validity of the findings, and whether or not it increased the study’s application to EBP

## To Prepare:

• Consider some of the important issues in healthcare delivery or nursing practice today. Bring to mind the topics to which you have been exposed through previous courses in your program of study, as well as any news items that have caught your attention recently. Select one topic to focus on for this Discussion.
• Review journal, newspaper, and/or internet articles that may provide credible information on your selected topic. Then, select one research article to focus on for this Discussion that used inferential statistical analysis (either a t-test or ANOVA) to study the topic.
• With information from the Learning Resources in mind, evaluate the purpose and value of the research study discussed in your selected article and consider the following questions:
• Who comprised the sample in this study?
• What were the sources of data?
• What inferential statistic was used to analyze the data collected (t-test or ANOVA)?
• What were the findings?
• Ask yourself: How did using an inferential statistic bring value to the research study? Did it increase the study’s application to evidence-based practice?

## By Day 3 of Week 5

Post a brief description of the topic that you selected for this Discussion. Summarize the study discussed in your selected research article and provide a complete APA citation. Be sure to include a summary of the sample studied, data sources, inferential statistic(s) used, and associated findings. Then, evaluate the purpose and value of this particular research study to the topic. Did using inferential statistics strengthen or weaken the study’s application to evidence-based practice? Why or why not? Be specific and provide examples.

## By Day 6 of Week 5

Read a selection of your colleagues’ responses and respond to at least two of your colleagues on two different days in one or more of the following ways:

• Ask a probing question, substantiated with additional background information, evidence, or research.
• Share an insight from having read your colleagues’ postings, synthesizing the information to provide new perspectives.
• Offer and support an alternative perspective using readings from the classroom or from your own research in the Walden Library.
• Suggest an alternative perspective based on additional evidence drawn from readings or after synthesizing multiple postings.
• Expand on your colleagues’ postings by providing additional insights or contrasting perspectives based on readings and evidence.

Week 5 Discussion Rubric

Post by Day 3 of Week 5 and Respond by Day 6 of Week 5

To Participate in this Discussion:

Week 5 Discussion

## 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.

## By Day 7

Submit your Assignment by Day 7 of Week 5.

### To submit your completed Assignment for review and grading, do the following:

• Please save your Assignment using the naming convention “WK5Assgn+last name+first initial.(extension)” as the name.
• Click the Week 5 Assignment Rubric to review the Grading Criteria for the Assignment.
• Click the Week 5 Assignment link. You will also be able to “View Rubric” for grading criteria from this area.
• Next, from the Attach File area, click on the Browse My Computer button. Find the document you saved as “WK5Assgn+last name+first initial.(extension)” and click Open.
• If applicable: From the Plagiarism Tools area, click the checkbox for I agree to submit my paper(s) to the Global Reference Database.
• Click on the Submit button to complete your submission.

Week 5 Assignment Rubric

Check Your Assignment Draft for Authenticity

To check your Assignment draft for authenticity:

Submit your Week 5 Assignment draft and review the originality report.

Submit Your Assignment by Day 7 of Week 5

To participate in this Assignment:

Week 5 Assignment

## What’s Coming Up in Week 6?

Photo Credit: [BrianAJackson]/[iStock / Getty Images Plus]/Getty Images

## Title: NURS 8201 Week 5 Assignment t-Tests and ANOVA WALDEN

Next week, you will continue your exploration of quantitative data. You will explore correlations and consider when it is best to utilize this statistical approach for quantifying relationships between variables.

Statistical analysis is a powerful tool that helps researchers gain valuable insights into a set of data and make informed decisions based on the results. Therefore, it is important for nurses and other professionals to have adequate knowledge regarding statistical analyses. There is also a need to know which statistical tests should be used based on the nature of the data set and the purpose of the analysis. Two types of statistical tests that have widely been applied in research are Analysis of Variance (ANOVA) and T-tests (Mishra et al.,2019). ANOVA is applied in to determine whether three or more groups or populations are statistically different. On the other hand, t-tests are applied to determine whether two groups are statistically different (Liang et al.,2019). Therefore, these two tests play a key role since they offer the researcher a chance to understand the nature of variations between variables in research. Therefore, the purpose of this assignment is to summarize the interpretation of the ANOVA statistics provided in the SPSS Output.

The data provided is on the overall satisfaction and material well-being. The data provided covers descriptive statistics, tests for homogeneity of variance, ANOVA and multiple comparisons. The descriptive table shows the standard deviation, mean and 95% confidence interval for the dependent variables for each separate group, which forms part of the study. From the data provided, the mean for “two or more housing problems” was 10.57, the mean for “one housing problem” was 11.97, and the mean for “No housing problem” was 12.71. The standard deviations observed for the three categories are 2.594, 2.588, and 2.353.  It is also important to note that the overall mean for all three groups represented in the study was 11.80.

Another important aspect of this data output is the test of Homogeneity of Variances. Levene’s test was used to accomplish this analysis. This analysis of the F-test when testing the null hypothesis that the variance is equal across all the groups tested (Yi et al.,2022). It is observable that the p-value obtained from Levene’s tests was 0.122, which means that they are not significantly different as the value is greater than 0.05.

The ANOVA output also showed the interaction within the group and between the groups of  “material well-being” and “overall satisfaction” as part of the statistical tests. From the results, it is evident that there was a statistically significant difference between the group means. The p-value obtained for this analysis is 0.000, a value above 0.05, indicating statistical significance. As such, the mean of material well-being and overall satisfaction is statistically significant. Nonetheless, it is not possible to have an idea of how the groups under consideration are different from each other using this test. As such, it is important to apply a computation of multiple comparisons with a Tukey post hoc test.

The next important part of the analysis is the multiple comparisons of “material well-being” and “overall satisfaction”, with a 0.05 used as the level of significance. The analysis shows that the difference between the means of the tested groups is statistically significant. As earlier indicated, a deeper study of the groups requires the use of Tukey post hoc tests, which is the test known and used in accomplishing post hoc tests on one-way ANOVA tests. Therefore, this study employed the Tukey post hoc test since it forms a vital ANOVA. When ANOVA is used to test the similarity of three or more groups’ means, the statistical significance results would show that not all the tested group means are similar (Uysal, et al., 2019).

The ANOVA output fails to identify the particular differences between the mean pairs that are significant. As such, the post hoc tests are key to determining the differences between the means of multiple groups while controlling the standard errors. The difference in overall satisfaction between one housing program and no housing problems was found to be 0.739, which is significant.  The difference in overall satisfaction between no housing problems and two or more housing problems was 2.139, which is also significant. In addition, the difference between one housing problem and two or more housing problems was 1.401, which is also significant.

It is also evident from the table that there was a statistically significant difference between one housing problem and no housing problem since the obtained p-value was 0.001. The p-value of 0.001 was obtained for the comparison of no housing problem and two or more housing problems means, which is also statistically significant. Besides, the difference between one housing problem and no housing problem was also statistically different, with a p-value of 0.001 observed.

## Conclusion

This assignment has focused on the t-tests and ANOVA for the provided data. The provided data was mainly on overall satisfaction and material well-being. Therefore, various analyses have been performed and reported. Descriptives, Tests of Homogeneity of Variance, ANOVA and multiple comparisons have all been explored.

## References

Liang, G., Fu, W., & Wang, K. (2019). Analysis of t-test misuses and SPSS operations in medical research papers. Burns & Trauma7. https://doi.org/10.1186/s41038-019-0170-3

Mishra, P., Singh, U., Pandey, C. M., Mishra, P., & Pandey, G. (2019). Application of student’s t-test, analysis of variance, and covariance. Annals of Cardiac Anaesthesia22(4), 407. https://doi.org/10.4103%2Faca.ACA_94_19

Uysal, M., Akyuncu, V., TanYıldızi, H., Sümer, M., & Yıldırım, H. (2019). Optimization of durability properties of concrete containing fly ash using Taguchi’s approach and Anova analysis.  DOI: 10.7764/RDLC.17.3.364

Yi, Z., Chen, Y. H., Yin, Y., Cheng, K., Wang, Y., Nguyen, D., … & Kim, E. (2022). Brief research report: A comparison of robust tests for homogeneity of variance in factorial ANOVA. The Journal of Experimental Education90(2), 505-520. https://doi.org/10.1080/00220973.2020.1789833

## Title: NURS 8201 Week 5 Assignment t-Tests and ANOVA WALDEN

### Nursing Shortages due to Covid

To provide a safe working environment, appropriate staffing must be maintained (CDC, 2021). According to the CDC (2021), as the Covid pandemic progresses, there will be staffing shortages due to healthcare personal (HCP), illness, or the need to care for family members at home. There are contingency capacity strategies to mitigate staffing shortages are being implemented (CDC, 2021). These strategies include cancelling all non-essential procedures and visits, attempting to address social factors that might prevent HCP from working, identifying additional HCP to work in the facility, and requesting that HCP postpone elective time off from work (CDC, 2021).

## ANOVA Study

Inferential statistics strengthen the study because it showed the amount of cases of infected populations from each country. This study reveled that The United States must take stronger precautions against Covid. This study was limited because it didn’t specify if there were any precautions were taken from each country. Studies are still showing that the U.S. cases of COVID-19 increased by 1,201,015 (a 41% increase) over a seven-day period. There is a daily case average of 168,409 cases, and Dec. 22 saw 242,794 new cases. The U.S. has exceeded 100,000 almost every day in December. North America had only 1,306,518 new cases. There were 8,876 new deaths over the past seven days for a 1% decrease. The U.S. has the highest number of new and total cases, the highest number of total deaths and new deaths (CDP, 2021)