Taks 1: remove categorical data and only leave numerical one. Please do it in sheet "Taskl" Task 2: For each of the features (not the target), try to nd outliers. You may use either IQR model, or use the z-score. Justify why you deleted some rows. Do it in Task2 page. Task 3: Build a multi-linear regression in Excel. What R2 value will you report? Reason which feature is the most important one in determining the yearly spent? Do it in Task3 sheet Task 4: Try "choosing" only some of the features. You may use correlation between features to remove some of the features, or use pvalue or tstat from previous linear regression task. Provide reason why you think removing some of the features, if any, can help. Please do in Task4 sheet Task 5: You have built two models so far, one with all features, and one with "less" number of features. How do you compare which model is better? Please do it inTaskS sheet Task 6: You can look at the residuals for both models where a histogram of residula (real values - predicted values) is plotted. Was assuming a linear model a good choice for this prediction, a valid assumption? Please do it in Task6