Some years ago, a large multinational company was accused of price manipulation of a particular commodity in violation of the Commodity Exchange Act. Multiple regression is sometimes used in litigation, such as ensued in this case. In a statistical study conducted for this case, a multiple regression model was developed to predict the price of the commodity 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 R2 was 0.989. For purposes ofthis assignment, assume 200 observations randomly selected from the time interval were used. Problem: The company in question had priced the commodity at $2.13. Their legal team needed to demonstrate that the price was not artificiallyr depressed. Requirements: 1. [2.5 points} For the relevant case, the fitted model gave the predicted value $2.136 with standard error $0.013. Based on this, determine a 95% prediction interval for the price of wheat. 2. [2.5 points} The judge in the case decided that the analysis provided evidence that the price was not artificially depressed, and the opinion was sustained by the court of appeals. Write a short summaryr of the results of the analysis that relate to the decision and explain why you agree or disagree with it.

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