Lecture: Introductory Statistics for Psychology

[@geordiebaden]

Timestamps: 00:00 Intro and lecture outcomes 1:45 What is a p-value? 2:20 What is a probability distribution? 9:37 Coin flip scenario; using a probability distribution and an alpha level 13:07 Null hypothesis significance testing 15:51 What is the null hypothesis in the coin flip example? 17:24 What is the alpha level in the coin flip example? 19:47 We've set up a null hypothesis significance test 20:20 Interpreting the result 22:12 What is the p-value in the coin flip example? 24:05 Null hypothesis significance testing in 5 steps 26:56 One- and two-tailed significance tests 31:06 Doesn't it remain possible that the coin is biased to produce heads? 31:43 Statistical power 38:28 The problem of low statistical power 44:50 How do we deal with low statistical power? 46:07 Recap: what is a p-value? 47:45 Fallacy #1: p is the probability that the null hypothesis is true 48:50 Fallacy #2: p is the probability of obtaining the observed data 50:58 Fallacy #3: small p indicates large effect size 53:39 Fallacy #4: p less than alpha means null hypothesis is false 54:38 Fallacy #5: p greater than alpha means the null hypothesis is true