Independent Samples t-Test System

An Independent Samples t-Test System is a two-sample t-test system or n-sample t-test system that implements an independent samples t-test algorithm to solve an independent samples t-test task.

• AKA: Unpaired Samples t-Tester.
• Context
  • Task Input: multi-dimensional sample dataset, population mean values.
  • Task Output: independent samples t-test statistic and p-value.
  • …
• Example(s):
  • a scipy.stats-based System.
    • stats.ttest_ind(rvs1,rvs2, equal_var = False) and stats.ttest_ind(rvs1, rvs3, equal_var = False) examples [1].
    • stats.ttest_ind(female_viq, male_viq) example [2].
    • stats.ttest_ind(a= minnesota_ages, b= wisconsin_ages,equal_var=False)[3]
• Counter-Example(s):
  • One-Sample t-Test System.
  • Paired Samples t-Test System.
• See: Parametric Statistical Test, Computing System, Parameter Optimization System.

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References

2017a

• (Scipy docs, 2017) ⇒ https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.ttest_ind.html
  • scipy.stats.ttest_ind(a, b, axis=0, equal_var=True, nan_policy='propagate')[source]

Calculates the T-test for the means of two independent samples of scores.

This is a two-sided test for the null hypothesis that 2 independent samples have identical average (expected) values. This test assumes that the populations have identical variances by default.

2017b

• (Varoquaux, 2017) ⇒ Retrieved on 2017-02-16 from "Statistics in Python" http://www.scipy-lectures.org/packages/statistics/index.html#student-s-t-test-the-simplest-statistical-test
  • QUOTE: We have seen above that the mean VIQ in the male and female populations were different. To test if this is significant, we do a 2-sample t-test with scipy.stats.ttest_ind()

2015

• (Hamelg, 2015) ⇒ Retrieved on 2017-02-26 from "Python for Data Analysis Part 24: Hypothesis Testing and the T-Test", http://hamelg.blogspot.ca/2015/11/python-for-data-analysis-part-24.html
  • QUOTE: A two-sample t-test investigates whether the means of two independent data samples differ from one another. In a two-sample test, the null hypothesis is that the means of both groups are the same. Unlike the one sample-test where we test against a known population parameter, the two sample test only involves sample means. You can conduct a two-sample t-test by passing with the stats.ttest_ind() function.

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