## 
## Call:
## lm(formula = Weekly_Sales ~ Temperature, data = trainlm, subset = CPI, 
##     weights = Fuel_Price)
## 
## Weighted Residuals:
##      Min       1Q   Median       3Q      Max 
## -1795734 -1654144   635985   938550  2044679 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 1528855.6    51297.1  29.804   <2e-16 ***
## Temperature   -1690.9      740.2  -2.284   0.0224 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1223000 on 4523 degrees of freedom
## Multiple R-squared:  0.001152,   Adjusted R-squared:  0.0009315 
## F-statistic: 5.218 on 1 and 4523 DF,  p-value: 0.0224

**The R^2 of the model is…

## [1] 0.002954389