Most of today was spent attempting to extract the actual Bootes II data from the data set. This was complicated by the fact that (as I realized after some time) some of the data points were duplicates, and some were just ridiculous and shouldn't even be counted. But with Beth's help I was finally able to narrow the 243 stars down to the 21 that are actually supposed to be in the galaxy. I then did my typical bootstrap/Nmix analysis.

But first I ran Nmix on the actual data, with the following results:

**Bootes II Nmix Results**

1) 21.3% confidence in 1 component, with mean of -122.9

2) 18.9% confidence in a 2 component fit, with means of -128.5 and -114.58

3) 14.2% confidence in 3 components

4) 10.4% confidence in 4 components

So these results are rather ambiguous, with no really obvious number of components. But that is probably a result of the small sample size of 21 stars. This is the least confident of all of the samples I have tested so far.

**Bootes II Bootstrap Nmix Results**

1) Only 15% had above 10% confidence for a single population, 5% above 20%

2) 25% of both the 2 and 3 component fits had a confidence above 10%

3) 10% had a 2 component fit with confidence above 20%, 5% of the 3's

4) However, in one of the 2 component best-fits where there was no chance of a single peak, 83% were in one of the peaks. Not sure where to make the cutoff that says the other peak is insignificant.

Overall, this was ridiculously inconclusive, but 2 components seems to win out.

To Do:

1) Learn more about bootstrapping/jack-knifing

2) Make a code that will read the Nmix data, then determine if the multi-component fit is significant or not based on the relative weights

3) Kurtosis

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