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Suppose you are trying to learn the relationship between the price you charge for your product and the likelihood of purchase by individuals offered that price. You offer your product online and for one month have randomly posted prices between $10 and $30. Using data on purchases and prices, you get the following estimates for a linear probability model:
Purchasei=1.7−0.06×Pricei
You are interested in the effect of a $20 price increase (i.e., moving from the lowest price to the highest) on the likelihood of Purchase. Why is answering this question problematic using this model?

Sagot :

Varshamittal029idn

The issue with this model is that purchases with a cost of $30 appear to be negative, which is impractical in real-world situations.

This is due to the model's linear best fit line's potential for being inaccurate for the end points.

A linear probability model:

Purchasei = 1.7-0.06×pricei

For an increase in $20 in price,

Change in purchase = -0.06 × 20

change in purchase = -1.2

There would be 1.2 less purchase.

Purchase at price of $10 is:

Purchase 10= 1.7 ×0.06 × 10

Purchase 10 = 1.1

Purchase at price of $30 is:

Purchase 30 = 1.7 × 0.06 × 30

Purchase 30 = -0.1

This is the problem with this model that the purchases at price of $30 is coming as negative which is not possible in practical situation.

It is because that the linear best fit line of the model which might not be accurate for the end points.

Hence we get the required estimates here:

Learn more about Estimate here:

brainly.com/question/28416295

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