What Arguments to use while doing a KS test in python with student's t distribution?
Question: I have data regarding metallicity in stars, I want to compare it with a
student's t distribution. To do this I am running a Kolmogorov-Smirnov test
using scipy.stats.kstest on python `KSstudentst =
scipy.stats.kstest(data,"t",args=(a,b))` But I am unable to find what the
arguments are supposed to be. I know the student's t requires a degree of
freedom (df) parameter but what is the other parameter. Also which one of the
two is the df parameter. In the documentation for scipy.stats.t.cdf the inputs
are the position at which value is to be calculated and df, but in the KS test
there is no sense in providing the position.


Answer: Those seem like the arguments for
[`scipy.stats.t.cdf`](http://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.stats.t.html):
`(df, loc=0, scale=1)` for standard t. Since they have default values, you
need to pass a tuple but it can be a singleton (`args = (2, )` for df=2)

    
    
    import scipy.stats as ss
    import numpy as np
    np.random.seed(0)
    data = np.random.randn(100)
    ss.kstest(data, "t", args = (2, ))
    Out[45]: KstestResult(statistic=0.093219139130061066, pvalue=0.33069879934011182)
    

Or passing loc=0 and scale=1, the same results:

    
    
    ss.kstest(data, "t", args = (2, 0, 1))
    Out[46]: KstestResult(statistic=0.093219139130061066, pvalue=0.33069879934011182)
    

