Type I vs. Type II Error (& Power)

This is the seventh (last!) video in a series on inferential statistics for PSY 200 and PSY 302. A Type I error is a false positive (finding an effect that isn’t there), and a Type II error is a false negative (failing to detect a real effect). This video discusses why acknowledging potential error is important, what each means, and how sample size increases power. For Video 1 on the Normal Distribution:    • Normal Distributions   For Video 2 on Sampling Distributions:    • From the Normal Distribution to Sampling D...   For Video 3 on Sampling Distributions and Statistical Inference:    • Sampling Distributions & Statistical Infer...   For Video 4 on p-Values & Null Hypothesis Testing:    • p-Values and Null Hypothesis Testing   For Video 5 on Confidence Intervals:    • Confidence Intervals   For Video 6 on Effect Size:    • Type I vs. Type II Error (& Power)