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Or what if I told you that the difference in weight loss was not statistically significant - the p-value was “only” 0.06 - but the average difference over the year was 20 pounds? You might very well be interested in that pill. Still interested? My results may be statistically significant but they are not practically significant. Now let me add that the average difference in weight loss was only one pound over the year. What if I told you that I had developed a new weight-loss pill and that the difference between the average weight loss for people who took the pill and the those who took a placebo was statistically significant? Would you buy my new pill? If you were overweight, you might reply, “Of course! I’ll take two bottles and a large order of french fries to go!”. P-values and statistical significance, however, don’t tell us anything about practical significance. The importance of research results is often assessed by statistical significance, usually that the p-value is less than 0.05.
#STATA 13 HOW TO#
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Many researchers in psychology and education advocate reporting of effect sizes, professional organizations such as the American Psychological Association (APA) and the American Educational Research Association (AERA) strongly recommend their reporting, and professional journals such as the Journal of Experimental Psychology: Applied and Educational and Psychological Measurement require that they be reported. Effects sizes concern rescaling parameter estimates to make them easier to interpret, especially in terms of practical significance. Today I want to talk about effect sizes such as Cohen’s d, Hedges’s g, Glass’s Δ, η 2, and ω 2.