Formulating and simulating a hypothesis

Statistical Thinking in Python (Part 2)

Justin Bois

Lecturer at the California Institute of Technology

2008 US swing state election results

ch3-1.002.png

¹ Data retrieved from Data.gov (https://www.data.gov/)

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Hypothesis testing

Assessment of how reasonable the observed data are assuming a hypothesis is true

Null hypothesis

Another name for the hypothesis you are testing

ECDFs of swing state election results

ch3-1.009.png

¹ Data retrieved from Data.gov (https://www.data.gov/)

Percent vote for Obama

ch3-1.011.png

¹ Data retrieved from Data.gov (https://www.data.gov/)

Simulating the hypothesis

ch3-1.013.png

¹ Data retrieved from Data.gov (https://www.data.gov/)

Simulating the hypothesis

ch3-1.015.png

¹ Data retrieved from Data.gov (https://www.data.gov/)

Simulating the hypothesis

ch3-1.017.png

¹ Data retrieved from Data.gov (https://www.data.gov/)

Simulating the hypothesis

ch3-1.019.png

Permutation

Random reordering of entries in an array

Generating a permutation sample

import numpy as np
dem_share_both = np.concatenate(
                       (dem_share_PA, dem_share_OH))

dem_share_perm = np.random.permutation(dem_share_both)

perm_sample_PA = dem_share_perm[:len(dem_share_PA)]
perm_sample_OH = dem_share_perm[len(dem_share_PA):]

Let's practice!

Statistical Thinking in Python (Part 2)