Merge pull request #497 from gungorMetehan/patch-8

Update 09-hypothesis-testing.Rmd

09-hypothesis-testing.Rmd

@@ -432,7 +432,7 @@ sampling_scenarios %>%
   column_spec(5, width = "1in")
 ```
 
-So, based on our sample of $n_m$ = `r n_resumes_gender` "male" applicants and $n_w$ = `r n_resumes_gender` "female" applicants, the *point estimate* for $p_{m} - p_{f}$ is the *difference in sample proportions* $\widehat{p}_{m} -\widehat{p}_{f}$ = `r p_men_promoted` - `r p_women_promoted` = `r observed_test_statistic` = `r observed_test_statistic*100`%. This difference in favor of "male" résumés of `r observed_test_statistic` is greater than 0, suggesting discrimination in favor of men. 
+So, based on our sample of $n_m$ = `r n_resumes_gender` "male" applicants and $n_f$ = `r n_resumes_gender` "female" applicants, the *point estimate* for $p_{m} - p_{f}$ is the *difference in sample proportions* $\widehat{p}_{m} -\widehat{p}_{f}$ = `r p_men_promoted` - `r p_women_promoted` = `r observed_test_statistic` = `r observed_test_statistic*100`%. This difference in favor of "male" résumés of `r observed_test_statistic` is greater than 0, suggesting discrimination in favor of men. 
 
 However, the question we asked ourselves was "is this difference meaningfully greater than 0?". In other words, is that difference indicative of true discrimination, or can we just attribute it to *sampling variation*? Hypothesis testing allows us to make such distinctions.