# 2 Running Head: STATISTICS PROJECT PART 3 Statistic Project Carla Pinkney PSYCH/625

2
Running Head: STATISTICS PROJECT PART 3
Statistic Project
Carla Pinkney
PSYCH/625
August 16, 2021
Mr. Matt Will
Statistics Project: ANOVA
After conducting the ANOVA data. I have realized that there is a convincing difference between the workers who have that positive engagement with their workplace happiness and the employer. The data indicates that if there is a positive relationship with the employer, the employees are more likely to be happy in the workplace. The f-ratio is larger than 396.12 that shows that there is huge difference between those two variables (Lee & Lee, 2020).
As I calculate the Tukey score, I can tell that the hypothesis is, in truth, proven, for the data is plain to show and specific. The ANOVA data analysis is much advantages over and above the t-test for to me, it is easier to understand, and also easier to compare the alternative effects of multiple variables. ANOVA gives a better data which can be used for future reference. ANOVA helps one to save time (Field & Wilcox, 2017).
Anova: Single Factor
SUMMARY
Groups
Count
Sum
Average
Variance
Column1
9
12
1.333333
0.25
Column 2
9
283
31.44444
20.77778
Column 3
9
21
2.333333
1.25
Anova
Ce of varia
ss
df
ms
f
p-value
Fcrit
Between
5265.407
2
2632.704
354.5287
1.52E-18
3.402826
Within gro
178.2222
24
7.425926
Total
5443.63
26
References
Field, A. P., & Wilcox, R. R. (2017). Robust statistical methods: A primer for clinical psychology and experimental psychopathology researchers. Behavior Research and Therapy, 98, 19–38. https://doi.org/10.1016/j.brat.2017.05.013
Lee, S., & Lee, D. K. (2020). What is the proper way to apply the multiple comparison test? Korean Journal of Anesthesiology, 73(6), 572–572. https://doi.org/10.4097/kja.d.18.00242.e1