ANOVA or T-test

I have two categorical variables as in below example:
Region	Dim	Value
PK	Dim1	2
PK	Dim2	3
PK	Dim3	-1
PK	Dim4	-4
US	Dim1	-0.5
US	Dim2	4.3
US	Dim3	2.1
US	Dim4	2
PK	Dim1	5
PK	Dim2	-0.4
PK	Dim3	-0.3
PK	Dim4	0.8
US	Dim1	1
US	Dim2	2
US	Dim3	0.8
US	Dim4	1
I want to compare the variables US and PK, if they are different from each other with respect to any or all of the four attributes (Dim1, Dim2, Dim3, Dim4). My question is:
1. Should I use a one way ANOVA and then post hoc (for example HSD Tukey) to determine if these two variables have any significant differences at any of these 4 attributes (PKDim1-USDim1, PKDim2-USDim2...)?
Since I have to report the results in 1 graph (box plot), i thought using an ANOVA would be fine. But, the issue of non-desirable group comparisons (e.g. PKDim1-PKDim2....) is confusing. Is it acceptable to perform ANOVA in such situations?
2. Should i just preform T-test 4 times, for example US versus PK on Dim1, Dim2, Dim3 and Dim4. And report each one separately.
Your helpful comments will be highly valuable.


TS Contributor
Since you only have two levels of region, either test will yield identical results with no need of a post-hoc test for the 1-way ANOVA. You would run either test once for each dependent variable (i.e., Dim1, Dim2,...), so you would not the non-desirable group comparisons.