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_posts/2024-02-15-berksons-paradox.md

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title: Berksons Paradox
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subtitle: More pitfalls of sampling
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image: /assets/blogs/berksons/sampled_data.png)
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image: /assets/blogs/berksons/sampled_data.png
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tags: [data-science]
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comments: false
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In this code I just set up a scatter plot with the randomly generated data.
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[![Random Data](/assets/blogs/berksons/total_data.png)]
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![Random Data](/assets/blogs/berksons/total_data.png)
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Then I give each of the four quadrants of the data a different probability of being sampled.
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[![Sampling Probabilities](/assets/blogs/berksons/sample_prob.png)]
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![Sampling Probabilities](/assets/blogs/berksons/sample_prob.png)
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When I do this sampling I then end up with a new scatter plot that makes it look like my data has a negative correlation.
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[![sampled Data](/assets/blogs/berksons/sampled_data.png)]
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![sampled Data](/assets/blogs/berksons/sampled_data.png)
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## So, what do?
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