Crash Course Statistics Statistics Correlation Doesn’t Equal Causation 2018
Today we’re going to talk about data relationships and what we can learn from them. We’ll focus on correlation, which is a measure of how two variables move together, and we’ll also introduce some useful statistical terms you’ve probably heard of like regression coefficient, correlation coefficient (r), and r^2. But first, we’ll need to introduce a useful way to represent bivariate continuous data - the scatter plot. The scatter plot has been called “the most useful invention in the history of statistical graphics” but that doesn’t necessarily mean it can tell us everything. Just because two data sets move together doesn’t necessarily mean one CAUSES the other. This gives us one of the most important tenets of statistics: correlation does not imply causation.
- Released: 2018-03-14
- Runtime: 13 minutes
- Genre:
- Stars: Adriene Hill
- Director:
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1. What Is Statistics 2018-01-24
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2. Mathematical Thinking 2018-01-31
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4. Measures of Spread 2018-02-14
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7. The Shape of Data: Distributions 2018-03-07
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8. Correlation Doesn’t Equal Causation 2018-03-14
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9. Controlled Experiments 2018-03-21
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10. Sampling Methods and Bias with Surveys 2018-03-28
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11. Science Journalism 2018-04-11
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13. Probability Part 1: Rules and Patterns 2018-04-25
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15. The Binomial Distribution 2018-05-09
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17. Randomness 2018-05-23
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18. Z-Scores and Percentiles 2018-05-30
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19. The Normal Distribution 2018-06-06
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20. Confidence Intervals 2018-06-13
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21. How P-Values Help Us Test Hypotheses 2018-06-27
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22. P-Value Problems 2018-07-11
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23. Playing with Power: P-Values Pt 3 2018-07-18
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24. You Know I’m All About that Bayes 2018-07-25
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25. Bayes in Science and Everyday Life 2018-08-01
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26. Test Statistics 2018-08-08
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27. T-Tests: A Matched Pair Made in Heaven 2018-08-15
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28. Degrees of Freedom and Effect Sizes 2018-08-22
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29. Chi-Square Tests 2018-08-29
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30. P-Hacking 2018-09-05
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31. The Replication Crisis 2018-09-26
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32. Regression 2018-10-03
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35. Fitting Models Is like Tetris 2018-10-24
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36. Supervised Machine Learning 2018-10-31
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37. Unsupervised Machine Learning 2018-11-07
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38. Intro to Big Data 2018-11-14
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39. Big Data Problems 2018-11-21
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40. Statistics in the Courts 2018-11-28
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41. Neural Networks 2018-12-12
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43. When Predictions Fail 2019-01-02
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44. When Predictions Succeed 2019-01-09
