t.test(x = _DATANAME_$_VARIABLE_, mu = _HYPOTHESIZED MEAN_, alternative = "_ALTERNATIVE HYPOTHESIS_")
tbl_1var(_DATANAME_, ~_VARIABLE_)
prop.test(x = _NUMBER OF SUCCESSES_, n = _SAMPLE SIZE_, p = _HYPOTHESIZED PROPORTION_, alternative = "ALTERNATIVE_ HYPOTHESIS")
infer_2mean_test(_DATANAME_, _VARIABLE_~_GROUPVARIABLE_)
Note: Confidence levels default to 95% but can be overridden with
conf_lvl = _DECIMAL_ (e.g.,
conf_lvl = 0.90).
infer_paired(_DATANAME_, var1 = ~_VARIABLE1_, var2 = ~_VARIABLE2_, conf_lvl = _CONFIDENCELEVEL_)
tbl_num_sum(_DATANAME_, _RESPONSE_~_GROUPVARIABLE_, na_rm = TRUE)
infer_anova(_DATANAME_, _VARIABLE_~_GROUPVARIABLE_)