Quality Kitchens Mix Report

1929 WordsAug 27, 20138 Pages
1 2 Table of Contents Executive Summary ................................................................................................... 3 Challenge ................................................................................................................... 3 Data Analysis ............................................................................................................. 3 Variables identification .......................................................................................................................... 3 Scatter Plots .......................................................................................................................................... 4 Correlation…show more content…
In the other hand, we notice that there is a non-linear distribution between Sales & Advertising (Appendix 1-Figure 3) which would lead us to build our regression model using the squared value of advertising as well as delayed advertising.. Correlation Before going forward and do additional analysis, we might consider looking at the multi-colinearity issues if any. In fact, the multi-collinearity problem does not result in biased coefficient estimates, but does increase the standard error of the estimates and thus reduces their reliability. According to (Appendix 2- Correlation), we notice a low correlation between explanatory variables: So there is no multi-collinearity issue. We keep all the presented independent variables and we carry out the regression so as to be able to go further in the analysis. Regression is very likely to be reliable after this correlation analysis. Regression We might now consider doing some regression analysis. In fact, the main objective of regression analysis is to explain variability of the dependent variable by means of one or more of independent or control variables. Regression 1 SUMMARY OUTPUT Regression Statistics Multiple R 0.95 R Square 0.90 0.78 Adjusted R Square Standard Error 52.12 Observations 23 Standard Error 239.216 0.806 0.785 0.727 0.749 2.329 34.354 0.000 35.727 33.706 Upper 95% 1260.099 8.238 -1.726 4.196 4.382 0.073 155.288 0.000 85.222 133.538 Intercept prom DelayedProm adv DelayedAdv index q1 q2
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