Final answer:
The coefficients b_1 and b_2 in the regression equation represent the slopes for x_1 and x_2, indicating how much y is expected to increase when each independent variable increases by one, while holding the other variable constant.
Step-by-step explanation:
The regression equation given is y=29.1270 + .5906x_1 + .4980x_2. In this equation, the coefficients b_1 and b_2 represent the slope of each independent variable x_1 and x_2 respectively. Specifically, b_1 = .5906 means that for every one-unit increase in x_1, the dependent variable y is expected to increase by about .5906 units, holding x_2 constant. Similarly, b_2 = .4980 indicates that for every one-unit increase in x_2, y is expected to increase by about .4980 units, holding x_1 constant.
To estimate y for specific values of x_1 and x_2, you would substitute those values into the equation. However, if the problem does not provide specific values for these variables, y cannot be estimated without further information.