The U.S. Bureau of Mines produces data on the price of minerals. Shown here are the average prices per year for several minerals over a decade. Use these data and multiple regression to produce a model to predict the average price of gold from the other variables. Comment on the results of the process. Gold Copper Silver Aluminum ($ per oz.) (cents per lb.) ($ per oz.) (cents per lb.) 161.1 64.2 4.4 39.8 308.0 93.3 11.1 61.0 613.0 101.3 20.6 71.6 460.0 84.2 10.5 76.0 376.0 72.8 8.0 76.0 424.0 76.5 11.4 77.8 361.0 66.8 8.1 81.0 318.0 67.0 6.1 81.0 368.0 66.1 5.5 81.0 448.0 82.5 7.0 72.3 438.0 120.5 6.5 110.1 382.6 130.9 5.5 87.8 *( Round the value of overall F and the standard error of the estimate to 2 decimal places.) **( Round the values of p to 3 decimal places.) ** *(Round the values of t to 2 decimal places.) ** **(Round the values of R2 and adjusted R2 to 1 decimal place.) The overall F for this model was * with a p-value of * * which is significant at o = .01. The t test for Silver is significant at o = .01 ( t = * * *, 0 =The t test for Aluminum yields a t = *** with a p-value of ** which is significant at o = .05. The t test for Copper was insignificant with a p-value of The value of R- was * * **% compared to an adjusted R2 of *** *0%. The gap between the two indicates the presence of some insignificant predictors (Copper). The standard error of the estimate is