Minitab2 - display For example, if you enter predictors in...

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Multiple Regression (1)Pre-analysis  Graph-Stem and leaf plot (‘increment’ is determined by the specific variable you want to plot) Graph-matrix plot—select the response and all the predictors  Correlation matrix:  Stat-Basic statistics-correlation- select the response and all the predictors  (correlation matrix is symmetric, please fill out the blank) (2) Regression—regression—select the response and predictors (the order of selecting the  predictors will matter in the Extra Sum of Squares Table), and then Graphs  (‘normal probability plot of residuals’; ‘fitted values versus response’; ’residuals versus  predictors’); Storage (‘fits’; ‘residuals’;’MSE’) Results (choose the third option which includes ‘sequential sum of squares…’) Sequential (or extra) sum of squares table is the last part of the ANOVA table in the result 
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Unformatted text preview: display For example, if you enter predictors in this order: x2, x1, x3 Then the extra sum of square table is as follows: (it is to calculate determination of partial correlation) SSR(x2) SSR(x1|x2) SSR(x3|x2,x1) e.g. R_{y1|2}=SSR(x1|x2)/SSE(x2), while SSE(x2) is obtained when you regress Y on x2 only (3) Confidence interval and Prediction interval RegressionregressionOptions If your model includes x1, x2, x3, Then in the prediction interval for new observation, enter values like 35(space)45(space)2.2 Then choose the right level (e.g. 90 or 95 or 99) Next choose both confidence limit and prediction limit...
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Minitab2 - display For example, if you enter predictors in...

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