Week 4: A. Assignment 6 (ANOVA)
This is only one of the multiple categorical variable to quantitative variable I could test with ANOVA. The one represented here is what I submitted.
The Variables:
armedforcesrate var [Armed Forces Personnel (% of total labor force)] v. oilperperson [Oil Consumption per capita]
Since both are quantitative variable, I have to turn one into a categorical variable. I also did this for the bar chart to represent better visually. The oilperperson variable is divided into four Q1, Q2, Q3, and Q4 as represented in the program below and named in OILGROUP.
The Hypothesis:
H0: There is no relationship between Armed Forces Personnel and Oil Consumption per Capita.
Ha: There is a relationship between Armed Forces Personnel and Oil Consumption per Capita.
Conclusion (ANOVA):
When examining the association between Armed forces rate (quantitative response variable) and Oil Group [consumption of oil per person in group] (categorical explanatory variable), an Analysis of Variance (ANOVA) revealed the association between the variables, F(3,52)=0.33, p=0.8041. Because my p value is greater than 0.05, I'm going to accept the null hypothesis, and say that these means are equal and there is no association between the Armed Forces Personnel and Oil Group.
Post Hoc Test:
Using Duncan's Multiple Range Test it is clear that there are NO statistically significant difference among the 4 oil groups.