is about has_specified_input has_specified_output achieves_planned_objective is denoted by has value Student's t-test study design dependent variable data transformation normal distribution hypothesis false positive rate Student's t distribution t-statistic study group population continuous variable between group comparison objective between group comparison statistical test two sample t-test with equal variance 2 true 1 Alejandra Gonzalez-Beltran scipy.stats.ttest_ind(a, b, axis=0, equal_var=True) http://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.ttest_ind.html#scipy.stats.ttest_ind source: https://github.com/scipy/scipy/blob/v0.15.1/scipy/stats/stats.py#L3271 Orlaith Burke Philippe Rocca-Serra adapted from: http://en.wikipedia.org/wiki/Student's_t-test#Independent_.28unpaired.29_samples and from: http://www.psychology.emory.edu/clinical/bliwise/Tutorials/TOM/meanstests/tind.htm t-test for independent means assuming equal variance t.test(x, y = NULL, alternative = c("two.sided", "less", "greater"), mu = 0, paired = FALSE, var.equal = TRUE, conf.level = 0.95, ...) http://stat.ethz.ch/R-manual/R-patched/library/stats/html/t.test.html two sample t-test two sample t-test is a null hypothesis statistical test which is used to reject or accept the hypothesis of absence of difference between the means over 2 randomly sampled populations. It uses a t-distribution for the test and assumes that the variables in the population are normally distributed and with equal variances. average value p-value ready for release