Multiple regression is sometimes used in litigation. In the case of Cargill, Inc. v. Hardin, the prosecution charged that the cash price of wheat was manipulated in violation of the Commodity Exchange Act. In a statistical study conducted for this case, a multiple regression model was developed to predict the price of wheat using three supply-and-demand explanatory variables. Data for 14 years were used to construct the regression equation, and a prediction for the suspect period was computed from this equation. The value of R2was 0.989. Problem: Cargill, Inc. had priced the wheat at $2.13. Their legal team needed to demonstrate that the price was not artificially depressed. For purposes of this project, suppose the sample size was 100.Requirements: 1.(2.5points) For the relevant case, the fitted model gave the predicted value $2.136 with standard error $0.013. Based on this, determine the 95% prediction interval for the price of wheat.