Problem: As a data analyst, you could use multiple linear regression to predict crop growth. You want to see how amount of rainfall, temperature, and amount of sunlight affects crop growth. An experiment with 20 sampling units was conducted obtaining the following data. Plot 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Crop Growth (mm/hr) 0.42 0.22 0.25 0.15 0.08 0.32 0.34 0.27 0.14 0.34 0.26 0.39 0.17 0.18 0.40 0.23 0.33 0.20 0.14 0.19 Rainfall (inches) 3.20 5.96 5.06 8.34 3.06 4.25 3.80 6.08 7.96 5.00 8.43 3.17 1.88 5.25 6.04 7.62 6.37 9.86 8.13 8.50 Temperature (°C) 34 18 22 13 27 19 23 32 35 30 39 19 40 16 13 17 20 9 11 9 Sunlight (hrs) 11 6 10 5 9 7 10 11 13 9 10 4 14 4 2 5 9 2 7 3 1. Identify the dependent and all independent variables. 2. Give the multiple linear regression model, in general form, for this problem and label your variables. 3. Compute for the partial regression coefficients, give the multiple linear regression with the coefficients and interpret the value of each coefficient. 4. Test the significance of the multiple linear regression model. 5. If the regression is significant in (4), identify which independent variable has significant contribution in describing the dependent variable. 6. Compute for R² and Rådjand interpret your results. 7. What would be the expected crop growth rate when the amount of rainfall is 0 inches, amount of temperature is 37°C, and amount of sunlight is 12 hrs.?