So this cannot be considered as a good model. Simple Linear Regression and Correlation: Analyses and Applications Multiple Linear Regression Other Topics in Applied Regression Analysis. Given this regression equation by Minitab, we still found that the R square is 97.6, which looks fine, however, the VIF value of chestgirth (13. Rest 44% of Variability is left unexplained. After finding the best subsets regression, we used Minitab to analyze the second predictive model after 10 predictor variables were excluded. Here, only 56.0% of Variability is explained by the model. This can be interpreted as ' 56.0% of Variability in the variable, price can be explained by all the independent variables together through this regression model. Thus we conclude that the overall regression model is significant at 1% level of significance.į) R-sq is called the coefficient of determination. The decision rule based on P-value is to Reject the null hypothesis if P-value is less than the level of significance. The 'Analysis of Variance' portion of the MINITAB output is shown below. We have already computed the value of F statistic and its P-value. The regression line generated by the inclusion of 'Sugars' and 'Fat' is the following: Rating 61.1 - 2.21 Sugars - 3.07 Fat (see Multiple Linear Regression for more information about this example). H 1 : The Regression model is significant. H 0 : The Regression model is not significant Thus we conclude that γis not significantly different from -0.5.Į) Here we are asked to carry out a F test. So, We fail to Reject the null hypothesis. From the Minitab, we get (61.173,69.584)) Æ We predict with 95 confidence that the height for a women with shoe size 8 to fall between 61.173 and 69.584 inches Regression Analysis: Height versus ShoeSize The regression equation is Height 46.0 + 2.42 ShoeSize Predictor Coef SE Coef T P Constant 46.014 2.593 17.74 0. The decision rule based on P-value is to Reject the null hypothesis if p value is less than alpha (0.05) Now, the P-value corresponding to t =1.41 and 96df from the t distribution table is 0.162

So, ø is not significant at 5% significance level. Here, P-value of bedroom = 0.742 and level of significance = 0.05 The decision rule based on p value is that the regression coefficient is significant if p value is less than level of significance. Here the P-value corresponding to (3,96) df from the F distribution table is approximately 0.Ĭ)Here, ø is the coefficient of variable, bedroom. Now, **** denotes the P-value of the F statistic. So, the P-value corresponding to 96 df and T=2.66 from the t distribution table is 0.009 Now, ** denotes the P- value of constant.

Regression analysis minitab