Please answer the questions for each section (4).

1. Introduction
-Introduce, describe, and/or provide context for the business case

2. Exercise Questions 1-3

-1Estimate the Cobb-Douglas function using regression analysis.

Recall that the Cobb-Douglas function is not a linear function; therefore, a log-linear function needs to be used to estimate this function. This requires that all the data must be converted into log format, base e. A simple conversion formula can be used to convert the data: =Log(Cell,Exp(1)), where Cell represents the cell location of the original data point. This formula should be applied to all the data before running the regression in Excel.

Once the data for the regression function has been generated, be sure to provide the regression equation in both log-linear form (Q = + 1lnL + 2lnK) and in Cobb-Douglas form (Q = L1K2). When converting the log-linear function into the Cobb-Douglas function, be sure to recalculate the numeric value of the intercept (). The following formula should be used to perform the recalculation: =Power(Exp(1),Cell), where Cell represents the cell location of the log-linear intercept value. Write out all the coefficients to three decimal places, except for the intercept value for the Cobb-Douglas function, which should be written out to five decimal places.

Based on Multiple R (correlation coefficient) and Adjusted R Square (coefficient of determination), evaluate the correlation of the data. Based on the F-value, evaluate the usefulness of the regression equation. Are the coefficients statistically significant? Explain.

3. Exercise Questions 4-5:

-Interpret the meaning of the coefficients for labor and capital. Provide an economic example/interpretation of their value. Does the production function exhibit increasing, constant, or decreasing returns to scale? Explain.

4. Conclusion:
Based on the regression output, what strategy would you advise the company to employ as it grows in its relevant market? Briefly explain your reasoning.

Please include the Excel output for the regression equation, copied into Word, as an appendix to the document.