Data for price and thickness of soap is entered into a statistics software package and results in a regression equation of ŷ = 0.4 + 0.2x. What is the correct interpretation of the slope if the price is the response variable and the thickness is an explanatory variable?
A. The price of the soap increases by $0.20, on average, when the thickness increases by 1 cm.
B. The price of the soap decreases by $0.40, on average, when the thickness increases by 1 cm.
C. The price of the soap increases by $0.40, on average, when the thickness increases by 1 cm.
D. The price of the soap decreases by $0.20, on average, when the thickness increases by 1 cm.

A. The price of the soap increases by $0.20, on average, when the thickness increases by 1 cm

Step-by-step explanation:

Given the following :

Regression equation : ŷ = 0.4 + 0.2x

Price is the response variable (ŷ)

Thickness is the explanatory variable (x)

Relating the equation given to the regression model:

ŷ = c + mx

Here c = intercept ; y = response variable ;x = explanatory variable and m = slope or gradient.

Hence, mx = 0.2x

Where m = 0.2

The slope means :

Change in y / change in x

Changes in the response variable with respect to change in the explanatory variable.

The slope is positive meaning an increase in the thickness will result in a corresponding increase in price.

With a 0.2 gradient value, that means there is an $0.2 average increase in price of soap as the thickness increases by 1 cm.

step-by-step explanation:

the answer is 24

step-by-step explanation: