# I need to respond to two of my peers

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Provide an example of an experiment or data that has two factors. Provide details (what is being measured and the number of levels) of the levels for factor A and factor B.

Refer to the Discussion Rubric for directions on completing these discussions.

Occupational Stress Chanel Tapper posted Sep 4, 2018 3:17 PM Hello All, An example of data that has to factors (and happens to currently hit home for me), is if an HR Dept. wants to know if occupational stress varies according to certain factors such as age and gender. Occupational stress would be the variable of interest and can be measured on a scale. The two factors for this data would be age and gender. Levels can vary depending on how the study is done, but age can be grouped into ranges (i.e. 21-30, 31-40, etc.) and these would be levels. Gender would also be classified as levels: male and female. This study’s hypothesis can be: Ho: All age groups have, on average, equal stress HA: Both genders have, on average, equal stress This, of course, are not the only hypothesis that can be tested, but that is an example. Discussion 8-1 Sean Delaney posted Sep 3, 2018 12:31 PM An example of two-way ANOVA is a clinical trial that would compare five different treatments for patients with osteoarthritis. Researchers would also like to analyze the differences in the treatment based on the gender of the patient. The two factors in the experiment are the treatment plan (5 levels) and the patient’s gender (2 levels). Researchers can investigate as to whether there are differences based on the prescribed treatment plan, by sex, or whether there is a difference in results by the combination or interaction of treatment and sex (LaMorte, 2016). The analysis of the two-factor ANOVA is similar to one-factor ANOVA, however the total variation is partitioned into that due to the main effect of treatment, the main effect of gender, and the interaction effect. Boston University gives the results below…… The ANOVA table above has four statistical tests. The first test is an overall test to assess whether there is a difference among the 6 cell means (cells are defined by treatment and gender). The F statistic is 20.7 and is highly statistically significant with p=0.0001. When the overall test is significant, focus then turns to the factors that may be driving the significance which would be the treatment plan or sex. The next three statistical tests analyze the significance of the main effect of treatment, the main effect of sex. and the interaction effect. In this example, there is a highly significant main effect of treatment (p=0.0001) and a highly significant main effect of sex (p=0.0001), and the interaction between the two does not reach statistical significance (p=0.91) (LaMorte, 2016). Reference LaMorte, W. (2016). Two-Factor ANOVA. Retrieved September 3, 2018, from http://sphweb.bumc.bu.edu/otlt/MPHModules/QuantCore/PH717_ANOVA/PH717_ANOVA6.html

MrMark
School: UT Austin

Hi, find attached.Regards

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Discussion Responses
Student’s Name
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DISCUSSION RESPONSES
Chanel Tapper
Great post with an excellent example of an experiment that has two variables. Stress is a
common issue with our places of work (Beehr, 2014). All of us acknowledge the fact that stress
can have great adverse effects on the organization’s performance as well as employees’ health.
In this case, you have given an example o...

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Anonymous
Goes above and beyond expectations !

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