Statistics

A researcher collected 28 observations of data in a project to predict the annual growth per acre of upland boreal forests in southern Canada. They hypothesized that cubic foot volume growth of upland boreal forests ( Y ) is related to the stand basal area per acre ( X1 ), the percentage of that basal area in black spruce ( X2 ), and the stand's site index for black spruce ( X3 ). The variation in the cubic foot volume growth of upland boreal forests was calculated at 200.70. The results from a multiple linear regression model fitted to the data is as follows: Variable Estimate P-value Intercept -19.39 0.0000 X1 0.59 0.0001 Xz 0.09 0.4320 X3 0.49 0.0040 In addition, R-square = 95.53% a) Give the fitted model based on the sample of data. Type in the answer with no spaces (you may use the notation x1 to represent 1 etc.): Y b) Which predictor variable has the highest effect on the cubic foot volume growth of upland boreal forests? () Construct the ANOVA table and use it to perform a hypothesis test for the overall fit of the estimated regression model using a 5% level of significance (Round each calculation to _ decimal places. DO NOT ROUND OFF VALUES OBTAINED FROM THE STATISTICAL TABLES)