Using the R-output data in the photo, test the significance of the individual parameters (test the H0 : ?i = 0 versus Ha : ?i ? 0, for ?1, ?2 and ?3).

Data on the sales of Wisconsin Lottery for 50 Zip code areas are analysed using R to investigate the relationship of the explanatory variables, POP (population in thou- sands), MEDINC (estimated median income in $1000s) and PERPERHH (persons per house hold) with the response variable SALES (online lottery sales to individual con- sumers) (Frees, 2010). The following model is proposed for this situation Y = Bo + BIX1+ 32X2 + B3X3 + E Where X1, X2 and X3 represent POP, MEDINC and PERPERHH respectively. The R-output for the fitted model is given below. Im(formula = SALES POP + MEDINC + PERPERHH) Coefficients: Estimate Std. Error t value Pr(> It1) (Intercept) -857.54502 7282.11368 -0.118 0.907 POP 0.60652 0.05854 10.361 1.3e-13 *** MEDINC 97.42212 69.29445 1.406 0.166 PERPERHH -994.41213 2967.25903 -0.335 0.739 Residual standard error: 3788 on 46 degrees of freedom Multiple R-squared: 0.7949, Adjusted R-squared: 0.7815 F-statistic: 59.42 on 3 and 46 DF, p-value: 7.39e-16