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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.

Questo esercizio fa parte del corso

Hypothesis Testing in Python

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Esercizio pratico interattivo

Prova a risolvere questo esercizio completando il codice di esempio.

# Conduct a t-test on diff
test_results = ____


                              
# Print the test results
print(test_results)
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