C532: ANOVA & Regression Modeling Dec 5, 2011 Y. Cao 1Topics: Learn how to use residual plot to assess model assumptions for multiple linear regression models and detect potential outliers and influential observations by influential graphics. Datasets: bodyfa.sav In a multiple linear regression, to assess the normality of the outcome variable we may use normal probability plot; to see if the variances are the same for each observation of the explanatory variable and for each treatment group then residual plotsin SPSS can help. To find possible outliers and influential observations we could follow the suggestions in today’s lecture note, for example, the scatter plot of Cook’s D or DfBetas, DfFits. If the Cook’s D is very large, we can remodel the data by excluding the outliers and/or influential observations that has the large Cook’s D values, and compare the models. The influential observations can be decided (by DeBetas’ DeFits) with the statistic values that have been given in the lecture note. We will realize some of these in our examples.
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