Crash Course Statistics - Season 1 Episode 21 : How P-Values Help Us Test Hypotheses

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Crash Course Statistics - Season 1 Episode 21

Crash Course Statistics 2018 -

Title: Crash Course Statistics - Season 1 Episode 21
Genre:
Country: United States of America
Studio: YouTube
Cast: Adriene Hill
Crew:
Alternative Titles:
Keyword: mathematics, educational, statistics, statistician

Overview:Today we're going to begin our three-part unit on p-values. In this episode we'll talk about Null Hypothesis Significance Testing (or NHST) which is a framework for comparing two sets of information. In NHST we assume that there is no difference between the two things we are observing and and use our p-value as a predetermined cutoff for if something seems sufficiently rare or not to allow us to reject that these two observations are the same. This p-value tells us if something is statistically significant, but as you'll see that doesn't necessarily mean the information is significant or meaningful to you.

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First Air Date: Jan 24, 2018 Last Air date: Jan 09, 2019 Season: 1 Season Episode: 44 Episode Runtime: 13:14 minutes Quality: HD IMDb: 9 / 10 by 1 users Popularity: 2.967 Language: en

Season 1

1. What Is Statistics2018-01-24
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2. Mathematical Thinking2018-01-31
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3. Mean, Median, and Mode: Measures of Central Tendency2018-02-07
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4. Measures of Spread2018-02-14
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5. Charts Are Like Pasta - Data Visualization Part 12018-02-21
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6. Plots, Outliers, and Justin Timberlake: Data Visualization Part 22018-02-28
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7. The Shape of Data: Distributions2018-03-07
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8. Correlation Doesn’t Equal Causation2018-03-14
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9. Controlled Experiments2018-03-21
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10. Sampling Methods and Bias with Surveys2018-03-28
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11. Science Journalism2018-04-11
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12. Henrietta Lacks, the Tuskegee Experiment, and Ethical Data Collection2018-04-18
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13. Probability Part 1: Rules and Patterns2018-04-25
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14. Probability Part 2: Updating Your Beliefs with Bayes2018-05-02
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15. The Binomial Distribution2018-05-09
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16. Geometric Distributions and The Birthday Paradox2018-05-16
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17. Randomness2018-05-23
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18. Z-Scores and Percentiles2018-05-30
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19. The Normal Distribution2018-06-06
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20. Confidence Intervals2018-06-13
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21. How P-Values Help Us Test Hypotheses2018-06-27
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22. P-Value Problems2018-07-11
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23. Playing with Power: P-Values Pt 32018-07-18
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24. You Know I’m All About that Bayes2018-07-25
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25. Bayes in Science and Everyday Life2018-08-01
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26. Test Statistics2018-08-08
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27. T-Tests: A Matched Pair Made in Heaven2018-08-15
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28. Degrees of Freedom and Effect Sizes2018-08-22
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29. Chi-Square Tests2018-08-29
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30. P-Hacking2018-09-05
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31. The Replication Crisis2018-09-26
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32. Regression2018-10-03
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33. ANOVA2018-10-10
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34. ANOVA Part 2: Dealing with Intersectional Groups2018-10-17
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35. Fitting Models Is like Tetris2018-10-24
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36. Supervised Machine Learning2018-10-31
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37. Unsupervised Machine Learning2018-11-07
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38. Intro to Big Data2018-11-14
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39. Big Data Problems2018-11-21
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40. Statistics in the Courts2018-11-28
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41. Neural Networks2018-12-12
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42. War2018-12-19
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43. When Predictions Fail2019-01-02
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44. When Predictions Succeed2019-01-09
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