How do statistics on fibre orientations measured with different acquisition schemes

Dear all,

I’m wondering which statistical approach I can use for comparing the the main directions per voxel (peaks) calculated from two different acquisitions schemes?
So in my work I do following measurements:

b-value | # gradient directions
1: 500 | 30, 20, 15, 10
2: 1000 | 60, 30, 20, 15
3: 1500 | 60, 20, 15
4: 2500 | 60, 40, 30, 20

Each measurement I want to repeat 5 times to get some statistic. So for example: 5x b_0=500 with 30 gradient directions, 5x b_0=500 with 20 gradient directions, 5x b_0=500 with 15 gradient directions and 5x b_0 =500 with 10 gradient directions. The same with every b-value and their gradient directions.

Out of these schemes I want to build me different shells (single and multi shells). For example: b_0=500 with 20 gradient directions and b_0=2500 with 40 gradient directions. So in the end I use always 60 gradient directions in total. To these schemes I want to do CSD (Mrtrix) and Bedpost (FSL) and compare the estimated directions. So for that I need a value or something else, so that I can compare at least something. I am not really into statistics so thank you for any kind of help
Here are my questions:

1.Which output I have to take from the approaches to compare and analyse the main directions? (I read that the peaks per voxel function from Mrtrix represents the main directions of the FOD and in Fsl I guess I have to take either the dyads files or the mean_phi,theta files? )

2.How can I calculate a statistical value like the mean or variance out of each 5 measurements?
Can I just calculate a mean vector and covariancematrices for each voxel and compare the different amount of their matrices traces or is this statistical incorrect?

3.How can I compare the estimated directions per voxel measured by two different schemes?
I do have some ideas: maybe calculate the angle differences or compare via calculating a distance metric? I guess I need always a reference direction (measurement) what could that be?.

Thank you!!