Forecasting case, Kwik Lube

(Kwik Trend Analysis) Measure         Value         time to come Period         Forecast Error Measures                  9.         1,362,143. Bias (Mean Error)         -0.0156         10.         1,455,952. MAD (Mean Absolute Deviation)         50,773.7969         11.         1,549,762. MSE (Mean square off up Error)         3,498,808,832.         12.         1,643,572. Standard Error (denom=n-2=6)         68,301.3828         13.         1,737,381. Regression soak up                  14.         1,831,191. lease (y) = 517857.2                  15.         1,925,000. + 93,809.5234 * Time (x)                  16.         2,018,810. Statistics                  17.         2,112,619. Correlation coefficient         0.9642         18.         2,206,429. Coefficient of determination (r^2)         0.9296         19.         2,300,238.                  20.         2,394,048.                  21.         2,487,857.                            Case-         kwik lubricating substance Question# 1 rate the loss for Kwik Lube stations during the last cardinal geezerhood using regression. How precise can the results claim to be? Question # 2 Was it worth $ 20000 to transact the marketing research? Question # 3 What otherwise factors might be introduced into the subject?                                                                                  Dick Johnson, an owner of the Kwik lubricator company, has leased DR. Gunn to file a lawsuit against T.A Williams after he had violate a franchise contract with Kwik Lube. To file a lawsuit Dr. Gunn was trying to abide by data about the alike(p) manufacturing or a exchangeable one in a mess a location resembling the area in which the buffer storage burner problem occurred. So, Dr.

Gunn decided to elate a data fro LA area. This would require the development of the questionnaire that could take the total gross assemble of cars serviced for fast oil and lubrication stock in the Los Angeles area amongst 1980 and 1990. Answer for # 1 question: Kwik Lube- Regression Model                           Demand Y         LA(X) 1         680,000         220000 2         750,000         250000 3         750,000         240000 4         780,000         260000 5         990,000         330000 6         1,040,000         350000 7         1,200,000         390000 8         1,330,000         440000                   Created by QM for Windows The following(a) table... If you want to get a full essay, set up it on our website: Orderessay

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