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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) +

Practical Management Science
Practical Management Science
6th Edition
ISBN:9781337406659
Author:WINSTON, Wayne L.
Publisher:WINSTON, Wayne L.
Chapter2: Introduction To Spreadsheet Modeling
Section: Chapter Questions
Problem 20P: Julie James is opening a lemonade stand. She believes the fixed cost per week of running the stand...
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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: 2 3 4 5 6 7 8 9 10 42.1 43.6 42.4 38.3 40.7 44.9 46.9 49.4 49.3 51.7 117 Month: PMI: Sale (1000s): 121 122 121 114 121 120 133 130 140 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 influences 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)+
Transcribed Image Text: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: 2 3 4 5 6 7 8 9 10 42.1 43.6 42.4 38.3 40.7 44.9 46.9 49.4 49.3 51.7 117 Month: PMI: Sale (1000s): 121 122 121 114 121 120 133 130 140 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 influences 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)+
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