Please help me unstuck

b. Use Least Square method to identify the Regression Line: Complete the table a decimal places 20:: my: s) = 2m :32 = 4 decimal places 4 decimal places {4 decimal places) (4 decimal places) Least square estimates of the slope (bl) = (4 decimal places) Intercept (b0) = (4- decimal places) Linear regression model (with the coefcient reported to the 3 decimal places) is 5' = bo(3 decimal places) + b1(3 decimal places): _ wrote9} _ . b1 E(x.--)' (3 dec'imal places) be = 51' b1 i , be = (4 decimal places) Practical Interpretation: what is the predicted oxygen purity assume it = 1.00 5* = % COEFFICIENT OF DETERMINATION: Complete the table Deviation 4 decimal 4 decimal 8 decimal 4 decimal 8 decimal places places places places places Sum (a decimal i :93} Sum [8 decimal . aces) 55.9 = 551' 555 55.9 = SSR 12 = SST r2 = percent of variability in y can be expalined by x = _ -% Correlation Coefficient: Txy = (sign of b,) Vrz Txy = We can conclude, in +0.9367, indicates there is a very strong positive linear relationship between x and y Hypothesis Test of Significance or the slope, t - test Ho(null hypothesis): Ha(alternative hypothesis)_ Test statistics: t - test = t = ~ where so, = Jy(x -2)2 and s = SSE In-2 =t = - b1 Sbi Use level of significance = 0.01 b1 + tasb, ta = find the value from the t distribution table: ttable = 99% Confidence Interval Estimate for the Slope, B1 SBIS Hypothesis Test of significance for the slope, t - test: Ho (null hypothesis): (State your null hypothesis) Ha(alternative hypothesis): (State your null hypothesis) Test statistics: =t = 1 = sb1 Critical value: ttable: Rejection rule Decision: Conclusion / Recommendation:1. in a chemical process. suppose that the yield of the product Is related to the process - operating temperature. As an illustration, 3; is the purity of oxygen produced in a chemical distillation process and x is the percentage of hydrocarbons present In the main condenser of the distillation unit. 1% \"-2