1. The following model was estimated to explain variability in wheat yields across a sample of 43 Kansas farms. Yield is measured in bushels/acre.

Yield= 100+ 0.05*Rain + 4.57*Fertilizer

1. Interpret each coefficient.

1. If the estimated coefficient on Rain is "unbiased", does this mean that the true value of the coefficient is 0.05? If not, what does "unbiased" mean?

1. If the estimated standard error of the coefficient on Fertilizer is 1.05, would you say that the coefficient is statistically significant at the 5% level? Provide a detailed explanation.

1. Suppose you now obtained additional dataset with 57 more farms and estimated the regression equation again. Describe in words whetherthe newly estimated standard errors would be greater or less than the previous ones. Discuss your reasoning.

1. Suppose the explained sum of squares (ESS) is equal to 750 and the total sum of squares (TSS) is equal to 1,230. Compute "R square" and "Adjusted R square" for this regression