A) Fit the model to the data and give the least squares prediction equation INPUT DATA INTO MINITAB - GENERAL REGRESSION = ( ) + ( )x + ( )x + ( )x Round to three decimal places as needed = B) Is there evidence that the first-order model is useful for predicting annual precipitation y? Test using a = 0.10. C) Predict, with 90% confidence, the average annual precipitation for station 9 FOR THIS GO TO STAT - REGRESSION - IN RESPONSE PUT IN THE Y VARIABLE AND IN THE PREDICTORS PUT IN THE X VARIABLES. GO TO OPTIONS AND PUT IN THE X VARIABLES IN THE PREDICTION INTERVALS AND CHECK CI AND PI AND MAKE SURE YOU HAVE THE RIGHT % Station y (in) x1(ft) x2 () 1 38.78 43 2 24.16 345 3 17.11 4154 4 38.74 75 5 49.14 6756 6 20.14 53 7 17.44 22 8 14.36 94 9 41.34 6358 10 13.73 79 x3 (mi) 46.7 40.1 34.1 39.2 39 37.8 38.2 37.3 36.5 36.9 1 96 68 1 152 5 78 26 143 10