NURS 8201 WEEK 5 ASSIGNMENT: T-TESTS AND ANOVA

Walden University NURS 8201 WEEK 5 ASSIGNMENT: T-TESTS AND ANOVA– Step-By-Step Guide

This guide will demonstrate how to complete the Walden University NURS 8201 WEEK 5 ASSIGNMENT: T-TESTS AND ANOVA assignment based on general principles of academic writing. Here, we will show you the A, B, Cs of completing an academic paper, irrespective of the instructions. After guiding you through what to do, the guide will leave one or two sample essays at the end to highlight the various sections discussed below.

How to Research and Prepare for NURS 8201 WEEK 5 ASSIGNMENT: T-TESTS AND ANOVA

Whether one passes or fails an academic assignment such as the Walden University NURS 8201 WEEK 5 ASSIGNMENT: T-TESTS AND ANOVA depends on the preparation done beforehand. The first thing to do once you receive an assignment is to quickly skim through the requirements. Once that is done, start going through the instructions one by one to clearly understand what the instructor wants. The most important thing here is to understand the required format—whether it is APA, MLA, Chicago, etc.

After understanding the requirements of the paper, the next phase is to gather relevant materials. The first place to start the research process is the weekly resources. Go through the resources provided in the instructions to determine which ones fit the assignment. After reviewing the provided resources, use the university library to search for additional resources. After gathering sufficient and necessary resources, you are now ready to start drafting your paper.

How to Write the Introduction for NURS 8201 WEEK 5 ASSIGNMENT: T-TESTS AND ANOVA

The introduction for the Walden University NURS 8201 WEEK 5 ASSIGNMENT: T-TESTS AND ANOVA is where you tell the instructor what your paper will encompass. In three to four statements, highlight the important points that will form the basis of your paper. Here, you can include statistics to show the importance of the topic you will be discussing. At the end of the introduction, write a clear purpose statement outlining what exactly will be contained in the paper. This statement will start with “The purpose of this paper…” and then proceed to outline the various sections of the instructions.

How to Write the Body for NURS 8201 WEEK 5 ASSIGNMENT: T-TESTS AND ANOVA

After the introduction, move into the main part of the NURS 8201 WEEK 5 ASSIGNMENT: T-TESTS AND ANOVA assignment, which is the body. Given that the paper you will be writing is not experimental, the way you organize the headings and subheadings of your paper is critically important. In some cases, you might have to use more subheadings to properly organize the assignment. The organization will depend on the rubric provided. Carefully examine the rubric, as it will contain all the detailed requirements of the assignment. Sometimes, the rubric will have information that the normal instructions lack.

Another important factor to consider at this point is how to do citations. In-text citations are fundamental as they support the arguments and points you make in the paper. At this point, the resources gathered at the beginning will come in handy. Integrating the ideas of the authors with your own will ensure that you produce a comprehensive paper. Also, follow the given citation format. In most cases, APA 7 is the preferred format for nursing assignments.

How to Write the Conclusion for NURS 8201 WEEK 5 ASSIGNMENT: T-TESTS AND ANOVA

After completing the main sections, write the conclusion of your paper. The conclusion is a summary of the main points you made in your paper. However, you need to rewrite the points and not simply copy and paste them. By restating the points from each subheading, you will provide a nuanced overview of the assignment to the reader.

How to Format the References List for NURS 8201 WEEK 5 ASSIGNMENT: T-TESTS AND ANOVA

The very last part of your paper involves listing the sources used in your paper. These sources should be listed in alphabetical order and double-spaced. Additionally, use a hanging indent for each source that appears in this list. Lastly, only the sources cited within the body of the paper should appear here.

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Sample Answer for NURS 8201 WEEK 5 ASSIGNMENT: T-TESTS AND ANOVA

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 & Trauma, 7. 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 Anaesthesia, 22(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 Education, 90(2), 505-520. https://doi.org/10.1080/00220973.2020.1789833

Sample Answer 2 for NURS 8201 WEEK 5 ASSIGNMENT: T-TESTS AND ANOVA

The quantitative study seeks to compare the efficacy of cognitive-behavioral therapy (CBT) and antidepressant medication in lowering depressed symptoms in patients receiving primary care. The research discovered that both therapies significantly reduced depressed symptoms compared to baseline after evaluating the data using inferential statistics like ANOVA. On the other hand, it was noted that patients who underwent both cognitive behavioral therapy (CBT) and psychopharmacological treatment reported more symptom relief than those who used just antidepressant drugs. According to this research, a combination of both cognitive behavioral therapy (CBT) and medication management are evidence-based intervention for treating depression in primary care settings.
Variables include the type of treatment, such as counseling, medication management, or both. The degree of depression, adherence to the treatment plan, and the existence of co-occurring mental or physical health issues, such as anxiety disorders, long-term illnesses (such as diabetes or cardiovascular disease), or drug use disorders, are some evidence-based variables that relate to depression.
Researchers can determine factors linked to good treatment outcomes and guide the development of individualized, evidence-based treatment modalities for patients with depression by analyzing the influence of these Evidence-Based Practice variables in the management of depression in primary care.

Sample Answer 3 for NURS 8201 WEEK 5 ASSIGNMENT: T-TESTS AND ANOVA

Article Description

With the COVID-19 pandemic, many colleges had to change their format to an online program instead of an in-person format. The article that I have selected discusses the switch to the online format and how nursing students feel about this change. It took a quantitative approach utilizing an online form to collect data from students to discover if they are satisfied with the online format and if there are any barriers that have been identified with this learning style. 

Summary of Sample Studied

The sample that was studied includes 219 nursing students. These nursing students are both undergraduate and graduate students. They are attending university in India. 

Data Sources

The data sources come from a questionnaire that the participants filled out. This questionnaire asked the demographic profile of the student filling out the questionnaire, their overall satisfaction with the program being online, and barriers that have been identified with the program being online. The satisfaction portion of the questionnaire had 15 items for study participants to fill out with categories ranging from highly dissatisfied to highly satisfied. The barriers portion had 20 items for study participants to fill out with always, sometimes, and never as options. 

Inferential Statistics used and associated findings

Inferential statistics help a researcher to draw conclusions from a sample to a population (Guetterman, 2019). Inferential statistics were used to analyze the data. This was used to help find the association of online learning and barriers related to the sociodemographic variables. 

Purpose and value of this research

The value of this research is helping to determine if the online learning model that many institutions were forced to adopt during the pandemic is something that can continue instead of moving back to the in-person model. By utilizing an online-only approach to learning, institutions can then employ instructors around the country instead of being limited to just the immediate vicinity that the institution is located in. This can also help the institution cut down on overhead costs by owning/renting fewer buildings. 

Did using inferential statistics strengthen or weaken this study’s application?

Utilizing inferential statistics is beneficial to researchers because they are able to make assumptions on data by using a smaller population, thus saving time and resources (Testbook, 2023). Using inferential statistics strengthened this study’s application. By better understanding what the barriers are related to online-only learning, institutions can help fix these to make online learning more beneficial to their students. For example, one of the biggest barriers that was noted in this study was a physical barrier such as eye strain. By identifying that this is a barrier that many students are noting with online classes, institutions can help to educate how to prevent eye strain and can also work to decrease eye strain themselves as well. 

References

Guetterman T. C. (2019). Basics of statistics for primary care research. Family medicine and community health, 7(2), e000067. https://doi.org/10.1136/fmch-2018-000067

Kumar, A., Kalal, N., Rana, N., Vyas, H., Choudhary, V., & Rani, R. (2021). Online learning in nursing students: Satisfaction and barriers. Journal of education and health promotion, 10, 411. https://doi.org/10.4103/jehp.jehp_1221_20

Testbook. (2023, May 23). Inferential Statistics: Definition, Types, Formulas with Examples. Testbook. https://testbook.com/maths/inferential-statistics#:~:text=Inferential%20statistics%20enables%20us%20to