In R [datarium package], the marketing dataset contains the impact of the amount of money spent on three advertising medias (youtube, facebook and newspaper) on sales. We want to build a model for estimating sales (y) based on the advertising budget invested in youtube (x1), facebook (x2) and newspaper (x3). Use the output provided to answer the questions below. After some trial and error, the following model was fit:1. Write down the multiple linear regression model from the regression analysis result. 2. This model is able to explain % of the observed variability in using its linear relationship with the other variables. 3. Interpret the slope coefficient of facebook in context. 4. Interpret the intercept coefficient in context. 5. Comment on the overall significance of the model, at a 0.05 significant level. 6. Design and conduct a hypothesis test to check if the variable newspaper in the context is significant, at a 0.05 significant level. (State your null hypothesis, test statistic, critical value, decision rule, conclusion) Possible critical values to be used: t(0.025,196)= 1.972141, t(0.05,196)= 1.652665, t(0.025,3)= 3.182446, t(0.025,3)= 2.353363.

> model summary (model) Call : Im(formula = sales ~ youtube + facebook + newspaper, data = marketing) Residuals : Min 10 Median 30 Max -10.5932 -1.0690 0. 2902 1.4272 3.3951 Coefficients : Estimate Std. Error t value Pr(>Itl) (Intercept) 3.526667 0. 374290 9.422