Stast basic

This is a module I developed to better understand the internal calculations on the basic statistical tests. The functions output a lot of text, but that is because learning is the goal here so I wanted to keep track of each step. There is a good amount of comments on the code as well. There is also a good chance that the functions are not 100% complete because I’ve not dealt with all possible scenarios;

Examples:

ANOVA:

>>> import statsbasic as sb
>>> labels = ['lab1', 'lab2', 'lab3', 'lab4']
>>> data =[[4.9, 5.7, 5.1, 5.3, 5.4, 5.5],
>>>        [5.4, 5.5, 4.8, 4.9, 5.2, 5.4],
>>>        [5.8, 6.0, 6.0, 5.5, 5.9, 5.8],
>>>        [4.5, 4.9, 4.7, 4.7, 4.4, 4.8]]
>>> dfObs = sb.CreateAnovaDataFrame(labels, data)
>>> sb.AnovaOneWay(dfObs)
>>> stats.f_oneway(data[0],data[1],data[2],data[3])

Chi Square:

>>> import statsbasic as sb
>>> data = np.array([
>>>     ['','A','B', 'C'],
>>>     ['Bought',109,49, 168],
>>>     ['Heard-no-buy',55,56, 78],
>>>     ['Never heard ',36,45, 54]
>>> ])
>>> dfObs = pd.DataFrame(data=data[1:,1:], index=data[1:,0], columns=data[0,1:]).apply(pd.to_numeric,axis=0)
>>> sb.ChiSquare_test(dfObs, debug=True)

One Sample T-Test:

>>> import statsbasic as sb
>>> sb.T_test_OneSample(2.9, 2.6, 0.4, 36, 0.05)
>>> SE(xbar): 0.067
>>> t statistic: -4.5
>>> t crit: +-2.03
>>> Reject Ho
>>> CI: [2.465, 2.735]

Tests Included and Signatures:

One sample t-test
- T_test_OneSample(mu, xbar, S, n, alpha, tail = 'two', direction = 'none')
Two Dependent Sample t-test (AKA paired comparison)
- T_test_TwoDependentSamples(xbar_sample_diffs, S_sample_diffs, n , alpha, tail = 'two', direction = 'none')
Two InDependent Sample t-test (AKA Between samples or Independent Samples)
- T_test_TwoInDependentSamples(xbar_A, xbar_B, StDev_A, StDev_B, nA, nB, alpha, tail = 'two', direction = 'none')
Proportions - CountDataSimpleTest
- CountDataSimpleTest (n, p, alpha=0.05)
Proportions - Two InDependent Sample t-test
- CountData_TwoInDependentSamples(pYes1, pYes2, pYesTotal, n1, n2, alpha)
Chi Square test
- ChiSquare_test(df, debug=False)
One Way ANOVA
- AnovaOneWay(dfObs)

dmenin / statsbasic