Assume you observed the following data from your operations. Once more, use a scaled version of the data, appropriately adjusting the units and scale to your specific product. Make sure you choose the appropriate units to get a realistic solution.

DAY	Q	L
	Number of robots assembled	Number of workers
1	25	5
2	299	7
3	427	8
4	417	11
5	438	12
6	946	13
7	197	6
8	43	6
9	524	14
10	668	12
11	341	15
12	722	13
13	511	7
14	278	9
15	302	7
16	34	5
17	475	12
18	37	5
19	289	8
20	305	8
21	447	11
22	806	7

In Excel, run a regression analysis for the following production function a to obtain the value of the parameters A and B: = 3 + 2 2. Interpret your results in the context of your project. Use your own words. This question is fundamental to how you interpret and relate these results to your business. 3. How well does the estimated represent the true Q? How do you know? What does it mean for your product/business? 4. Do the parameter estimates have the appropriate algebraic signs? Why is this important in the context of your business? 5. Are the parameters statistically significant at the 5 and 1 percent levels of statistical significance? What does it mean regarding your product? How is this important for your business? 6. At what level of labor usage does the average product reaches its maximum value? How is that important to know in the context of your business? 7. What is the average cost when the average product is maximized? What does it mean regarding your product? How is this important for your business? 8. What is the short-run marginal cost when the average product is maximized? What does it mean regarding your product? How is this important for your business? 9. Beyond what level of labor employment does the Law of Diminishing Returns sets in? Beyond what level of output? What does it mean regarding your product? How is this important for your business?