h. Explore the relationship between spending and each of the two continuous predictors by creating two scatterplots (SPENDING vs. FREQ, and SPENDING vs. LAST UPDATE). Does there seem to be a linear relationship?I c. To t a predictive model for SPENDING: i. Partition the HID-l] records into training and validation sets. [Note that the dataset has a validation columu create your om validation column for this exercise.) ii. Run a multiple linear regression model for SPENDING vs. all six predictors. I{'ilive the estimated predictive equation. iii. Based on this modelI 1what type ofpurchaser is most likely to spend a large amount ofmoney'? iv. Ifwe used backward elimination to reduce the number of predictors, which predictor would he dropped rst time the model? v. Show how the prediction and the prediction error are computed for the rst purchase in the validation set. vi. Evaluate the predictive accuracy of the model by examining its performance on the validation set. vii. Create a histogram of the model residuals. Do they appear to follow a normal distribution? How does this affect the predictive performance of the model'iI