Question

A candy bar manufacturer is interested in trying to estimate how sales are influenced by the price of their product. To do this, the company randomly chooses 6 small cities and offers the candy bar at different prices. Using candy bar sales as the dependent variable, the company will conduct a simple linear regression on the data below: What is the estimated average change in the sales of the candy bar if price goes up by $1.00?

Answer 1

Answer:

-48.19

Step-by-step explanation:

Given the data:

City Price ($) Sales

River Falls 1.30 100

Hudson 1.60 90

Ellsworth 1.80 90

Prescott 2.00 40

Rock Elm 2.40 38

Stillwater 2.90 32

We could obtain a simple regression model of the data above using a linear regression calculator :

The regression model obtained is :

ŷ = -48.19277X + 161.38554

The change in sales per unit change in price is the value of the slope or gradient :

From the general linear regression equation :

y = mx + c

m = slope ;

Slope = - 48.19 ; hence, there is a drop in sales by about 48 units as the change in sales as the price of candy bar goes up by about $1.00