has part has_specified_input has_specified_output achieves_planned_objective is denoted by has value statistical hypothesis test objective Student's t-test study design independent variable study design dependent variable data transformation normal distribution hypothesis false positive rate Student's t distribution dichotomous variable paired t-test 1 true 1 true scipy.stats.ttest_rel(a, b, axis=0) http://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.ttest_rel.html#scipy.stats.ttest_rel source: https://github.com/scipy/scipy/blob/v0.15.1/scipy/stats/stats.py#L3389 Alejandra Gonzalez-Beltran Orlaith Burke Philippe Rocca-Serra http://stat.ethz.ch/R-manual/R-patched/library/stats/html/t.test.html t.test(dependent variable ~ independant variable, data = dataset, var.equal = FALSE, paired= TRUE) http://udel.edu/~mcdonald/statpaired.html http://udel.edu/~mcdonald/statsignedrank.html paired t-test is a statistical test which is specifically designed to analysis differences between paired observations in the case of studies realizing repeated measures design with only 2 repeated measurements per subject (before and after treatment for example) t-test for dependent means t-test for repeated measures subject pairing t-statistic within subject comparison statistical test continuous variable within subject comparison objective p-value ready for release