Forecasting case, Kwik Lube

(Kwik Trend Analysis) Measure         Value         Future Period          judge 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 up Error)         3,498,808,832.         12.         1,643,572. Standard Error (denom=n-2=6)         68,301.3828         13.         1,737,381. Regression line                  14.         1,831,191. Demand (y) = 517857.2                  15.         1,925,000. + 93,809.5234 * sentence (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 Lube move# 1 arrange the loss for Kwik Lube stations during the last two old age using regression. How accurate can the results claim to be? nous # 2 Was it worth $ 20000 to perform the marketing research? Question # 3 What otherwise factors might be introduced into the subject?                                                                         !          nib Johnson, an owner of the Kwik lube company, has leased DR. Gunn to file a instance against T.A Williams after he had violate a Franchise foreshorten with Kwik Lube. To file a lawsuit Dr. Gunn was trying to find entropy about the same manufacturing or a similar one(a) in a location a location resembling the field of operation in which the pilot burner problem occurred. So, Dr. Gunn decided to collect a data fro LA area. This would require the development of the questionnaire that could determine the agree gross piece of cars serviced for fast oil and lubrication business in the Los Angeles area amongst 1980 and 1990. Answer for # 1 question: Kwik Lube- Regression sit around                           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: BestEssayCheap.com

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