a. Construct a causal regression model using PMIl as the causal variable. How well does your model fit the data? (Enter r-squared as decimal (not percent). Round your answers to 2 decimal places.) Sales (1000s)= R = (PMI) + b. Suppose that the PMI is truly a leading indicator. That is, the PMI value in one period influence's sales in the following period. b-1. Construct a new regression model using this information. (Enter r-squared as decimal (not percent). Round your answers to 2 decimal places.) Sales (1000s) = R2 = (PMI) +

a. Construct a causal regression model using PMIl as the causal variable. How well does your model fit the data? (Enter r-squared as decimal (not percent). Round your answers to 2 decimal places.) Sales (1000s)= R = (PMI) + b. Suppose that the PMI is truly a leading indicator. That is, the PMI value in one period influence's sales in the following period. b-1. Construct a new regression model using this information. (Enter r-squared as decimal (not percent). Round your answers to 2 decimal places.) Sales (1000s) = R2 = (PMI) +

Purchasing and Supply Chain Management

6th Edition

ISBN:9781285869681

Author:Robert M. Monczka, Robert B. Handfield, Larry C. Giunipero, James L. Patterson

Publisher:Robert M. Monczka, Robert B. Handfield, Larry C. Giunipero, James L. Patterson

Chapter2: The Purchasing Process

Section: Chapter Questions

Problem 4DQ

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