HLT 362 Week 4 Understanding Analysis of Variance (ANOVA) and Post Hoc Analyses

HLT 362 Week 4 Understanding Analysis of Variance (ANOVA) and Post Hoc Analyses

HLT 362 Week 4 Understanding Analysis of Variance (ANOVA) and Post Hoc Analyses

There are a few different ways to conduct an ANOVA test in SPSS. The first way is to use the “ANOVA” command. To do this, go to “Statistics” and then select “ANOVA.” After selecting this option, a dialog box will appear. Next, select the variable that you want to use as the dependent variable and click “OK.” Another way to conduct an ANOVA test in SPSS is to use the “Regression” command (van den Bergh et al., 2020). To do this, go to “Statistics” and then select “Regression.” After selecting this option, a dialog box will appear. Next, select the variable that you want to use as the dependent variable and click ” OK. When conducting an ANOVA to see if there is a statistically significant difference in the Interval Depression Score among 3 groups of shift workers, one may want to first ensure that the data meets the assumption of normality. This can be done by running a goodness-of-fit test, such as the Kolmogorov-Smirnov test (Liu & Wang, 2021). If the data meet the assumption of normality, one can proceed with conducting the ANOVA. The null hypothesis for this test is that there is no difference in the Interval Depression Scores among the three groups of shift workers. The alternative hypothesis is that there is a difference in at least one of the group means. The purpose of this assignment is to conduct an ANOVA to see if there is a statistically significant difference in the Interval Depression Score among 3 groups of shift workers.

Having Trouble Meeting Your Deadline?

Get your assignment on HLT 362 Week 4 Understanding Analysis of Variance (ANOVA) and Post Hoc Analyses  completed on time. avoid delay and – ORDER NOW

Part One

  1. Identify the independent and dependent variables.

While conducting ANOVA test, it is necessary to determine both the dependent and independent variables. In this case, the independent variable is Shift Worked while the dependent variable is Depression Score (Interval).

online nursing essays

Struggling to Meet Your Deadline?

Get your assignment on HLT 362 Week 4 Understanding Analysis of Variance (ANOVA) and Post Hoc Analyses done on time by medical experts. Don’t wait – ORDER NOW!

  1. Write a null hypothesis.

H0: There is no statistical significance between the depression score and the shift worked.

  1. Write an alternative non-directional hypothesis.

H1: There is a statistical significance between the depression score and the shift worked.

  1. Interpret your results. Guidelines for interpreting ANOVA results can be found in
Table 1: ANOVA
Shift Worked (nominal) 1=first, 2=second, 3=third
Sum of Squares df Mean Square F Sig.
Between Groups 10.267 12 .856 1.672 .162
Within Groups 8.700 17 .512
Total 18.967 29

Click here to ORDER an A++ paper from our Verified MASTERS and DOCTORATE WRITERS: HLT 362 Week 4 Understanding Analysis of Variance (ANOVA) and Post Hoc Analyses

Table 1 shows ANOVA output between the dependent and independent variables identified in the study. The significant value generated is 0.162 which is greater than 0.05 level of significance i.e., 0.162> 0.05, as a result, we fail to reject the null hypothesis. We therefore conclude that There is no statistical significance between the depression score and the shift worked.

Part Two

ANOVA is a statistical technique that is used to test for differences between groups. In this case, we are looking at the Interval

hlt 362 week 4 understanding analysis of variance (anova) and post hoc analyses
HLT 362 Week 4 Understanding Analysis of Variance (ANOVA) and Post Hoc Analyses

Depression Score (IDS) among three groups of shift workers. The ANOVA analysis will help us determine if there are any significant differences between the IDS scores of the different groups (Akbay et al., 2019). To carry out the ANOVA analysis, we first need to gather data from each of the three groups of shift workers. We will need to know the mean IDS score for each group, as well as the number of people in each group. Once we have this information, we can plug it into an ANOVA calculator (there are many freely available online).

The significant value generated is 0.162 which is greater than 0.05 level of significance i.e., 0.162> 0.05, as a result, we fail to reject the null hypothesis. We therefore conclude that There is no statistical significance between the depression score and the shift worked. There are a number of possible explanations for why there is no statistical significance between the depression score and the number of shifts worked. It could be that the sample size is too small to detect a difference, or that the relationship between depression and shift work is more complex than a simple linear relationship. Another possibility is that other factors, such as job satisfaction or social support, play a larger role in determining depression among workers who do shift work.

Conclusion

The significant value generated is 0.162 which is greater than 0.05 level of significance i.e., 0.162> 0.05, as a result, we fail to reject the null hypothesis. From the study conducted, there is no statistical significance between the depression score and the shift worked. There are a few different ways to conduct an ANOVA test in SPSS. The first way is to use the “ANOVA” command. To do this, go to “Statistics” and then select “ANOVA.” After selecting this option, a dialog box will appear.

HLT 362 Week 4 Understanding Analysis of Variance (ANOVA) and Post Hoc Analyses

References

Akbay, L. O. K. M. A. N., Akbay, T., Osman, E. R. O. L., & Kilinc, M. (2019). Inadvertent Use of ANOVA in Educational Research: ANOVA is not A Surrogate for MANOVA. Journal of Measurement and Evaluation in Education and Psychology10(3), 302-314. https://doi.org/10.21031/epod.524511

Liu, Q., & Wang, L. (2021). t-Test and ANOVA for data with ceiling and/or floor effects. Behavior Research Methods53(1), 264-277. https://link.springer.com/article/10.3758/s13428-020-01407-2

Van den Bergh, D., Van Doorn, J., Marsman, M., Draws, T., Van Kesteren, E. J., Derks, K., … & Wagenmakers, E. J. (2020). A tutorial on conducting and interpreting a Bayesian ANOVA in JASP. LAnnee psychologique120(1), 73-96. https://www.cairn.info/revue-l-annee-psychologique-2020-1-page-73.htm?ref=doi

Topic 2 DQ 2

Using the research article selected for DQ 1, identify three key questions you will ask and answer when reading the research study and why these questions are important. When responding to peers, provide other questions and answers that could be considered in relation to the peers’ studies.

REPLY TO DISCUSSION

Unread

The research study I selected in DQ 1 was “Spiritual and Religious Issues of Stigmatization Women with Infertility: A Qualitative Study: Spiritual and Religious Issues of Stigmatization” by Akarsu & Beji in 2021. Three key questions that I will ask about the research selected are as follows:

Question 1: What is the significance of this study?

Response:

The significance of this study was to determine the perceptions of women with infertility on stigma and religious and spiritual issues of stigmatization (Akarsu & Beji, 2021). The desire to have children is the focal point of women’s physical well-being. As a result, issues linked to raising children are viewed as flaws in women. Women’s social obligation to have children affects how their infertility is considered (Forsythe, as cited in Akarsu & Beji, 2021). Deficiency in reproductive functions causes social stigmatization due to cultural norms, beliefs, and values. Infertility is an important issue for both sexes because it is an instinctive biologic behavior to have offspring, but also an important issue to be a family as a part of a community. It is also an important issue for medical caregivers working in infertility to deal with and determine the psychological aspects of infertility.

Question 2: How was the data collected?

Response:

The data was collected by conducting a 30- 60-minute interview, which consisted of open-ended questions. Subjects were interviewed in a quiet and calm room near the polyclinics. The researcher transcribed interviews during the interview since none of the issues gave consent for voice recording (Akarsu & Beji, 2021). Data were coded, and related themes were formed using the content analysis method. These themes included reasons for experiencing infertility, current emotional states, families’ reactions to infertility, people’s general opinions about women with infertility, and the effects of meeting with people who were aware of their stigma.

Question 3: What was the method of sampling?

Response:

This qualitative study was conducted with the voluntary participation of women diagnosed with infertility and monitored in the obstetrics and gynecology polyclinics at the Bozok University Practice and Research Hospital (Akarsu & Beji, 2021). The phenomenological method was used for the study consisting of a research sample of 12 women with infertility selected through the criterion sampling method (Yıldırım [26] as cited in Akarsu & Beji, 2021). The phenomenological approach aims to describe, understand and interpret the meanings of experiences of human life. It focuses on research questions such as what it is like to experience a particular situation (Bloor & Wood, 2006). Criterion sampling involves selecting subjects that meet some predetermined criterion of the study.

Reference:

Bloor, M. & Wood, F. (2006). Phenomenological methods. In Keywords in qualitative methods (pp. 129-130). SAGE Publications Ltd, https://www.doi.org/10.4135/9781849209403

Höbek Akarsu, R., & Kızılkaya Beji, N. (2021). Spiritual and Religious Issues of Stigmatization Women with Infertility: A Qualitative Study: Spiritual and Religious Issues of Stigmatization. Journal of Religion and Health, 60(1), 256–267. https://doi- org.lopes.idm.oclc.org/10.1007/s10943-019-00884-w

Ryan, Christina. (2018). Population and Sampling Distributions. Retrieved from:

https://lc.gcumedia.com/hlt362v/applied-statistics-for-health-care/v1.1/#/chapter/2

Similar Posts