Session Ready
Exercise

Using ttest()

Manually calculating test statistics and transforming them with a CDF to get a p-value is a lot of effort to compare two sample means. The comparison of two sample means is called a t-test, and the pingouin Python package has a .ttest() method to accomplish it. This method provides some flexibility in how you perform the test.

As in the previous exercise, you'll explore the difference between the proportion of county-level votes for the Democratic candidate in 2012 and 2016 to identify if the difference is significant. The hypotheses are as follows:

\(H_{0}\): The proportion of democratic votes in 2012 and 2016 were the same. \(H_{A}\): The proportion of democratic votes in 2012 and 2016 were different.

sample_dem_data is available and has the columns diff, dem_percent_12, and dem_percent_16 in addition to the state and county names. pingouin and has been loaded along with pandas as pd.

Instructions 1/4
undefined XP
  • 1
  • 2
  • 3
  • 4
  • Conduct a t-test on the sample differences (the diff column of sample_dem_data), using an appropriate alternative hypothesis chosen from "two-sided", "less", and "greater".
Loading