Final answer:
In the estimated regression equation, b1 represents the change in y for each one-unit increase in x1, and b2 represents the change in y for each one-unit increase in x2. The y-intercept can be calculated using the slope and median values of x and y.
Step-by-step explanation:
The equation given is y = 29.1270 + .5906x1 + .4980x2. In this estimated regression equation, b1 and b2 are the coefficients for the independent variables x1 and x2 respectively. The coefficient b1 (equal to .5906) represents the expected change in the dependent variable y for each one-unit increase in the first independent variable x1, holding all other variables constant. Similarly, the coefficient b2 (equal to .4980) represents the expected change in y for each one-unit increase in the second independent variable x2, again holding all other variables constant.
The y-intercept of a regression line (denoted as 'a' in the formula y = a + bx) can be found by substituting the median of the x values and the given slope into the formula b = ymedian - m * xmedian. For example, if the sum of the median x values is 1264 and the sum of the median y values is 219.5, and if the slope (m) is approximately 0.09, we would calculate the y-intercept as b = 219.5 - 0.09(1264), which simplifies to b≈ 35.25. Therefore, the line of best fit would be represented as y = mx + b.