3. According to the regression equation, we predict the number ofhotus spent watching TV per week to declease by as the number ofhours spent working per week increases by 4. Based on the regression equation. what would be the predicted number of hours of Ti." watched per week for a student who works Ell] hours per week? 5. \"iii of the variability in hours spent watching TV per week can be explained by the regression equation, and \"it: of the variability.r in hours spent watching TV per week cannot he explained by the regression equation. Part 2: More reasoning about Elam, correlation: and Egression Data was gathered from a random sample offast-food items. From each item, researchers obtained the amount of sodium {in milligrams. or mg} and the number of calories. The scatterplot below displays the relationship between sodium content and number of calories. The regression equation and the value ofr! are given below the scatterplot. Predicted number of calories = 183.5 + 0.35 {sodium content} 1"! = 54.29%