Situation:
The U.S. Bureau of Mines produces data on the price of Minerals. The data below displays the average prices per year for several minerals over a decade.
Gold ($ per oz.) Copper (cents per lb.) Silver ($ per oz.) Aluminum (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
Action:
Use the attached MS Excel spreadsheet data and multiple regression to produce a model to predict the average price of gold from other variables. Comment on the following:
- Regression equation
- R, R2 and 1-R2, adjusted R2
- Standard error of estimate
- Report the t's for each value and the corresponding p-values
- Overall test of hypothesis and decision
- Use a .05 level of significance. Cite which variables are significant and which are not significant, based on the t values and p values for each independent variable.