The following regression equation for quantity supplied was estimatedusing a sample of fifty observations.
Q = 2.2 + 0.104P. (3.4) (0.005)
Standard errors are in the brackets. The total sum of squares was 132 and the residual sum of squares was 19.5
Calculate and interpret R-square. What other factors could possibly explain
variations in the quantity supplied?
R-square is calculated by taking the ratio of the total sum of squares (132) to the residual sum of squares (19.5). This gives an R-square of 0.85, which indicates that 85% of the variation in the quantity supplied can be explained by the regression equation.
Other factors that could explain variations in the quantity supplied include the price of related goods, the availability of substitutes, the cost of production, the level of consumer income, and the level of consumer confidence.