1. Multiple Regression Using the data in the file "Data for HW4Q1 Due Feb 16 2022" posted on Brightspace, determine a model equation relating the dependent variable (Y) to the 5 predictor variables in which all terms are statistically significant at the 95% confidence level using Excel. You should clearly show your model equation, the coefficients and the error in those coefficients with appropriate significant figures. 2. Based on your answer to question 1, what is the average value of Y for a set value of x1 = 25 and x2=15? Give an estimate of the error (or range) in the calculated value. Make sure to use appropriate significant figures. 3. Non-linear Regression Your boss is interested in the sorption of a chemical into soil and she remembers reading about Freundlich isotherms and that they describe the mass of solute sorbed per unit mass of soil as a function of the concentration of the solute in the liquid phase. Your boss wants to know what data needs to be collected and how it should be plotted and regressed using Excel in order to determine the parameters in the Freundlich isotherm. Your boss remembers that non-linear regression is a good approach to fitting data and so wants you to use that approach. Provide a detailed response to your bosses question with an example. Y 2x. IX x12x2 OSZ 10 20 30 40 100 400 500 750 006 0091 0001 x2 $ 5 5 5 3 10 10 10 10 x112 50 100 150 200 250 100 200 300 400 OS 25 25 25 25 25 100 100 100 100 100 2500 100 400 20 I OE 900 40 01 005 1600 2500 100 400 00 95.111 94.577 94.714 94317 94644 90.8 90.183 91341 91.321 92.104 72.422 82.089 84.937 878 89.941 62.963 76.126 84 855 87.694 90.556 55.298 78 262 84.624 87.078 400 1250 1000 2000 3000 4000 5000 4000 1000 12000 16000 20000 10 20 30 40 888888888888888888888885 00 99999999999999999 006 200 400 600 800 1000 300 400 400 1600 2500 100 400 0006 006 006 20 20 20 20 20 30 30 30 30 30 40 40 40 40 009 18000 10 20 30 40 50 900 006 22000 16000 900 006 900 1200 1500 400 MOO 1200 1600 nnn 1600 2500 100 400 01 20 30 40 1600 1600 1600 TO ten 45000 16000 32000 48000 64000 00 1600 an