To determine whether price has an impact on sales of specialty coffees, the managers kept track of how many pounds of each variety of coffee were sold last month. PRICE PER POUND POUNDS SOLD
Mean $8.75 4.50 lb
Standard Deviation $3.63 18.33 lb
Correlation r -.927

a. The response variable is and the explanatory variable is
b. Based on the statistics shown above, the slope of the estimated regression line that relates the response variable to the predictor variable is:

i. 0.846.
ii. -4.681
ii. -0.858.
iv. 45.459
v. -8.999.

A. Response Variable is POUND SOLD Explanatory variable is PRICE PER POUND

B. ii. -4.681

Step-by-step explanation:

A. Based on the statistics that was shown in the given information above the:

Response Variable is POUND SOLD Explanatory variable is PRICE PER POUND

B. Calculation to determine slope of the estimated regression line that relates the response variable to the predictor variable

Using this formula

Slope =r*Sy/Sx

Let plug in the formula

Slope=-0.927*18.33/3.63

Slope=-16.99191/3.63

Slope=-4.681

Therefore , the slope of the estimated regression line that relates the response variable to the predictor variable is: -4.681

constant of proportionality = 3 and the equation is c = 3p.

step-by-step explanation:

c = kp   where c = amount of caffeine in mg., p = oz of pepsi and k is the constant of proportionality.

substituting the values given:

24 = 8k

k = 3.

the same value of k will be obtained if we substitute the other given values.

yx = 36

step-by-step explanation:

cos f = opposite side/ hypotenuse

cos f = yw / yx

we know cos f = 4/9 and yw =16

4/9 = 16/yx

multiply each side by yx

4/9 yx = 16/ yx * yx

4/9 yx = 16

multiply each side by 9/4

9/4 * 4/9 yx = 16 *9/4

yx = 36