Effect Size, Probability & Hypothesis testing

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  • Effect Size, Probability & Hypothesis testing
    • Effect Size
      • A general term for describing the thing we are interested in finding
      • Cohen's D
        • An effect size that expressed difference between two means in standard deviation units
        • d = (M1 -M2)/?((SD12+SD22)/2)
      • How meaningful, impactful, influential is our effect
        • Ranges on a numerical continuum; often has cut-offs for “small,” “medium,” and “large”
      • Not affected by sample size
    • Probability
      • Probability distribution
        • A curve describing an idealised frequency distribution of a particular variable from which you can get the probability
    • Null Hypothesis Significance Testing
      • an approach to evaluating our findings
      • Experimental/ alternative hypothesis = effect. 
      • Evaluating the degree to which the data are incompatible with a model summarised by “the null hypothesis”
    • alpha value
      • the cut-off at which we decide whether we can reject the null hypothesis
      • If p ?, then we typically cannot reject the null hypothesis
    • Statistical power
      • the probability that we will reject the null hypothesis when it is appropriate to do so
      • affected by sample size 
    • Type I and Type II error
      • Type I = False positive
      • Type II = False negative


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