Scenario 2: Below is a multiple regression in which the dependent variable is market value of houses and the independent variables are the age of the house and square footage of the house. The regression was estimated for 42 houses.

SUMMARY OUTPUT

Regression Statistics
Multiple R 0.745495
R Square 0.555762
Adjusted R Square 0.532981
Standard Error 7211.848
Observations 42

ANOVA
df SS MS F Significance F
Regression 2 2537650171 1.27E+09 24.39544 1.3443E-07
Residual 39 2028419591 52010759
Total 41 4566069762

Coefficients Standard t Stat P-value Lower95%Upper95%
Error
Intercept 47331.38 13884.34664 3.408974 0.001528 19247.6673 75415.0958
House Age -825.161 607.3128421 -1.35871 0.182046 -2053.5662 403.243744
SquareFeet 40.91107 6.696523994 6.109299 3.65E-07 27.3660835 54.4560534

Refer to Scenario 2 above. What is the estimated regression equation for determining the market value of houses?

Refer to Scenario 2. If the age of a house increases by 1 year given that the square feet is held constant, what is the impact on the house's market value?

Solution Summary

A Complete, Neat and Step-by-step Solution is provided.

In the regressionequation, what does the letter "b" represent?
Y intercept
Slope of the line
Any value of the independent variable that is selected
Value of Y when X=0

From a management policy perspective, which regression result is the most useful?
a regressionequation that passes the F-test.
a regressionequation whose explanatory variables all passed the t-test.
a regressionequation that has the highest R2.
a regressionequation that has the least n

The presence of autocorrelation leads to all of the following undesirable consequences in the regression results except:
a the least-squares estimates of the regression coefficients will be biased
b the t-statistics may yield incorrect conclusions concerning the significance of the individual independent variables

Managerial Economics Assignment
Below are data on quantity produced at a group of shirt manufacturing plants. Each plant also reports its total cost. This exercise tests your knowledge of empirically verifying economic theory of short-run production cost.
a. What is the theoretical regressionequation of the short-run to

This is a portion of the solution. Please see attachment for full problem and solution:
In their article, "The Demand for Coffee in the United States: 1963-1977" (Quarterly Review of Economics and Business, Summer 1980 pp.36-50), C.J. Huang, J.J. Siegfried, and F. Zardoshty estimated the following regressionequation using qu

When is a regressionequation used? What terms describe the fit of a regressionequation to the data? What is the importance of the coefficient of determination (r2)?
What are outliers? How do you identify outliers in your data? How do outliers impact your regressionequation?

Regression analysis was used to estimate the following linear trend equation:
St = 10.5 + 0.25t
Use this equation to forecast the value of the dependent variable (St) in time period of 10.
10.75
13
35.5
2.5