Interpreting Regression Results-Loss Prediction (Appendix): Johnstar Company makes an expensive chemical product. The costs average about $1,000
Question:
Interpreting Regression Results-Loss Prediction (Appendix): Johnstar Company makes an expensive chemical product. The costs average about $1,000 per unit of weight. and the material sells for $2,500 per unit of weight. Materials storage is extremely hazardous; therefore, a batch is made each day to fill customers' needs for the day. Failure to deliver the required quantity results in a shutdown for the customers, with a corresponding cost penalty assessed against Johnstar. However, excess chemicals on hand at the end of the day must be disposed of in costly, secure facilities. The chemical increases in weight during processing, but the exact increase varies depending on temperature and pressure conditions as well as on the impurities present in the input materials. It is important for the company to know the final weight from any batch as soon as possible so that a new batch can be started should the expected final weight be smaller than required for customer needs. A consultant was hired to advise the company on how to estimate the final weight of the product. The consultant recommended that the product be weighed after three hours and that the weight after three hours be used to predict the weight at the end of processing. Based on 20 processed batches, the following observations were made:
Data obtained from the regression analysis included the following:
Required:
a. Use the results of the regression to calculate the estimate of the final weight of today's batch, which at the end of three hours weighs 42 units.
b. (Knowledge of statistics required.) Customer orders for today total 68 units. The smallest batch that can be started must weigh at least 20 units at the end of three hours. What factors should be considered in deciding whether to start a new batch?
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