Question

I posted this earlier. I need help with how to do each step.

I don’t know where to begin. Can you explain as you go and answer the questions please?

Excel Project 1 Purchasing Merchandise Number of Department Purchased Purchase Number cost in SIA] inSIBI Orders IC] Suppliers IDI 2,059,000 119,566,000 5,944 1,533,000 68,315,000 4,357 1,066,000 33,505,000 2,793 1,622,000 139,312,000 1,707 875,000 128,811,000 2,125 1,110,000 33,456,000 2,550 1,755,000 38,674,000 3,617 539,000 29,854,000 1,327 557,000 1,729,000 2,523,000 877 1,519,000 86,225,000 1,954 1,548,000 102,875,000 7,586 1,267,000 130,944,000 4,731 190 132 Miami Baltimore New York Toronto Detroit Chicago St. Louis Phoenix Los Angeles Houston San Francisco Seattle Vancouver 208 121,160,000 1,433 168 168 104 201 Q1. Run an OLS regression of A on B. Q2. Run an OLS regression of A on C. Q3. Run an OLS regression of A on D. Q4. Find the best cost driver for the cost of the Purchasing Department. Q5. What are your decision criteria? Q6. According to your regression model, what is a variable cost and a fixed cost of A? Q7. How much variations in A were explained by your cost driver? Q8. What is the relevant range of your model?

Answer 1

Q1. Let the equation has the form A_i = $\alpha$ + $\beta$ B_i + U_{i Where} $\alpha$ and $\beta$ are the parameters, U is the disturbance term.

To run an OLS regression of A on B

Since this is an excel project, first you type the data in an excel worksheet use the following steps:

Step 1: Type the data on A and B into two columns (The variable name must be given into the first row)

Step 2: Click the data analysis tab on the tool bar menu( you should installed the data analysis tool pack )

Step 3: A pop up window will appear. Click regression among the options of pop up window.

Step 4: another pop up window (namely Regression will appear).

Select the data on variable A (in Input Y range box) and select data on B variable (in the Input X range box).

Step 5: select the location where your output ranged.

Step 6: click Ok.

Excel will calculate the linear regression and gibe the results.

The result sheet is posted bellow

Q.2 To run the OLS regression of A on C you will type the data on A and C. Then repeat the above steeps. You will obtain the results as

Q.3 OLS regression of A on D.

Q.4. To answer the question we will concentrate on the value of R² in each of the regression. Because R² measures the proportion of total variation explained by the regression.

Viz, In regression A on B, R² = 0.105712. This means that 10.5712 % of the variation of the values of variable A can be explained by variable B.

Similarly, for second case R² = 0.217947. i.e, 21.7947% of total variation of variable A can be explained by the variable C.

By the way, 43.0237 % of total variation of variable A can be explained by the variable D

Since, variable D can explain a greater percent of the variation of A. Therefore, numbers of suppliers is the best cost driver for the cost of the purchasing department. .