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Saturday, July 20, 2013

Forecasting case, Kwik Lube

(Kwik Trend Analysis) Measure         Value          future(a) 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 whole up Error)         3,498,808,832.         12.         1,643,572. Standard Error (denom=n-2=6)         68,301.3828         13.         1,737,381. Regression tonal pattern                  14.         1,831,191. adopt (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 lubricator Question# 1 rate the loss for Kwik Lube stations during the last two geezerhood using regression. How unblemished can the results claim to be? Question # 2 Was it worth $ 20000 to action the marketing research? Question # 3 What otherwise factors might be introduced into the subject?                                                                                  Dick Johnson, an owner of the Kwik lubricate 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 sense data about the same(p) manufacturing or a kindred one in a view a location resembling the area in which the original burner problem occurred. So, Dr.
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Gunn decided to attract a data fro LA area. This would require the development of the questionnaire that could restrict the total gross percentage of cars serviced for fast oil and lubrication melodic phrase 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 side by side(p) table... If you want to get a full essay, set up it on our website: Ordercustompaper.com

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