Construct a causal regression model

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Reference no: EM131919681

Question: Many supply managers use a monthly reported survey result known as the purchasing managers' index (PMI) as a leading indicator to forecast future sales for their businesses. Suppose that the PMI and your business sales data for the last 10 months are the following:

a. Construct a causal regression model using PMI as the causal variable. How well does your model fit the data?

b. Suppose that the PMI is truly a leading indicator. That is, the PMI value in one period influences sales in the following period. Construct a new regression model using this information. Is the new model better or worse than the model you made for part a?

c. Pick the best model from parts a and b, and create a forecast for sales given PMI = 47.3.

Reference no: EM131919681

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