It is often useful to decision makers at a company to determine what factors enter into the size of a customer's purchase. Suppose decision makers at Virginia Semiconductor want to determine from past data what variables might be predictors of size of purchase and are able to gather some data on various customer companies. Assume the following data represent information gathered for 16 companies on five variables: the total amount of purchases made during a one-year period (size of purchase), the size of the purchasing company (in total sales volume), the percentage of all purchases made by the customer company that were imports, the distance of the customer company from Virginia Semiconductor, and whether the customer company had a single central purchasing agent. Use these data to generate a multiple regression model to predict size of purchase by the other variables. Summarize your findings in terms of the strength of the model, significant predictor variables, and any new variables generated by recoding. Size of purchase ($1,000) comp. size ($million sales) % of customer imports distance from vsi Central purchases
27.9 25.6 41 18 1
89.6 109.8 16 75 0
12.8 39.4 29 14 0
34.9 16.7 31 117 0
408.6 278.4 14 209 1
173.5 98.4 8 114 1
105.2 101.6 20 75 0
510.6 139.3 17 50 1
382.7 207.4 53 35 1
84.6 26.8 27 15 1
101.4 13.9 31 19 0
27.6 6.8 22 7 0
234.8 84.7 5 89 1
464.3 180.3 27 306 1
309.8 132.6 18 73 1
294.6 118.9 16 11 1