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  3. Causal Inference with R - Experiments

Exercise

Oregon Health Experiment Data: Balance Checks

Now that we've created separate dataframes for the treatment and control groups, let's do some balance checks between the groups to see if they are sufficiently balanced to allow for our comparisons. Run a t-test between the two groups, examine the results, and decide whether the t-test is statistically significant by analyzing its confidence interval. In real analysis, you'll check for statistically significant balance on more than just one variable, but we'll just stick with gender for this set of questions.

Instructions

100 XP
  • 1) Run a t-test to see if there is a statistically significant difference in gender between the treatment and control groups (i.e. whether gender is balanced between the treatment and control group).
  • 2) After looking at the confidence interval of the t-test, can we say the t-test results are statistically significant? Answer "yes" or "no".