Crash Course Statistics Statistics Episode 23 Playing with Power: P-Values Pt 3 2018
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We're going to finish up our discussion of p-values by taking a closer look at how they can get it wrong, and what we can do to minimize those errors. We'll discuss Type 1 (when we think we've detected an effect, but there actually isn't one) and Type 2 (when there was an effect we didn't see) errors and introduce statistical power - which tells us the chance of detecting an effect if there is one.
- Released: 2018-07-18
- 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
