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.
This exercise is part of the course
Hypothesis Testing in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Conduct a t-test on diff
test_results = ____
# Print the test results
print(test_results)