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Statistical Inference, Inferential Statistics, Hypothesis Testing, Probability Levels, Statistical Tests, One Tailed Test, Two Tailed Test, Directional Test, Non Directional Test, Improper Interpretation and many other learning points are available in this lecture.
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Understanding Research Results - Statistical Inference Inferential Statistics Mean difference = true difference Probability levels Hypothesis testing Hypothesis Testing Statement regarding how two variables are related Null Hypothesis: μ 0 = μ (^1) Research Hypothesis: μ 0 ≠ μ (^1) Statistical Tests t-test and F-test t-test is appropriate when you have 1 IV with 2 levels Ratio Numerator: Mean difference Denominator: Random error Degrees of Freedom Divisor used to compute the estimated population variance
F-test An extension of the t-test Used when you have more than 1 IV with 2 groups Relationship between t and F: Ratio of systematic & error variance Type I and Type II Errors Reject the null, but the null is true p value is the probability of making a Type I error Accept the null, but the null is false probability of making a Type II error is related to power Type III and Type IV Errors Type III Error Getting the direction wrong Type IV Error Improper interpretation of an interaction What Does “ p < .05” Mean? Low probability differences were due to random error p = .05 does not mean that 5 times out of 100 you would get a different result. p(H:E) p value tells us “p(E:H)” What is the probability of obtaining a dead person (D) given that this person was hanged(H)? p(D:H) This is what a p value tells us