Please explain The following R output is obtained from a multiple linear regress
ID: 3243290 • Letter: P
Question
Please explain The following R output is obtained from a multiple linear regression analysis y = beta_0 + beta_1 + beta_2x_2 + elementof, where E(elementof) = 0, Var(elementof) = sigma^2 and observations (x_1i, x2i, y_i), i = 1, 2, .... n are independent and identically distributed in which we are interested in the effects of temperature (denoted by x_1) and pressure (denoted by x_2) on the rate of reaction (denoted by y) in a reaction chamber. Call: lm(formula = y ~ xl + x2) Residuals: Min IQ Median 3Q Max - 0.89961 -0.44920 -0.04601 0.32086 1.44655 Coefficients: Multiple R-squared: 0.9815, Adjusted R-squared: 0.816 What is your conclusion for the hypothesis test that there is no effect of the temperature on the rate of reaction? What is the estimated regression line for the effect of the temperature and pressure on the rate of reaction? In the context of this problem, if we fix the pressure value to 0 and we increase the temperature 1 unit, how much change do we expect in the rate of reaction? What percentage of the variability in the data is explained by the estimated regression line? What is the predicted value of the rate of reaction when temperature value is 0. and the pressure value is 0?Explanation / Answer
(a) Since P value of x1 (0.037) is less than 0.05 level, we conclude that there is significant effect of temperature on rate of reaction
(b) Estimated Regression line y = 2.053+0.910x1+4.844x2
(c) The Change will be 0.910 unit
(d) 98.15% variability can be explained by the estimated regression line. (since R^2 is 0.9815)