The data gives the values of the 29 teams in the National Basketball Association, along with their operating incomes and revenues. Plots and correlations show that revenue predicts team value much better than does operating income. The least-squares regression line for predicting value from revenue is as follows: value = -123.298 + 4.242 revenue (a) What is the slope of this line?: 4.242 (b) The HORNETS are the NBA's most valuable team, valued at $547 million, with $147 million in revenue. Use the line to predict the value of the HORNETS from their revenue. What is the error in this prediction?: -123.298 + (4.242 * 147) = 500.276 547 - 500.278 = 46.724 (c) What is the correlation of revenue and value?: r = ?

4.242;

$500.276 ; $46.724

Step-by-step explanation:

Given the regression equation :

value = -123.298 + 4.242 revenue

y = - 123.298 + 4.242x

y = team value ; x = Revenue

(a) What is the slope of this line?

From ;

y = mx + c

Where ; m = slope

Comparing the equation with, the model equation ;

mx = 4.242x ; Hence, slope, m = 4.242

(b) The HORNETS are the NBA's most valuable team, valued at $547 million, with $147 million in revenue. Use the line to predict the value of the HORNETS from their revenue.

Predicted value of hornets based on their revenue :

Revenue = $147,000,000

y = - 123.298 + 4.242(147)

y = - 123.298 + 623.574

y = 500.276

Predicted value is about $500.276 million.

What is the error in this prediction?:

Error = Actual - predicted value

Error = 547 - 500.276 = $46.724 million

option 1 is correct.

step-by-step explanation:

y varies inversely with x and constant of variation is 4

the equation will be:

y = k/x

where k =4 so,

y = 4/x

if we put values of x of option 1 in the above equation and find values of y

y = 4/-2 => y =-2

y = 4/-1 => y = -4

y = 4/1 => y = 4

y = 4/2 => y =2

so, all the values of x and y are correct.

if we put values of x given in other options and find value of y we cannot find whole table satisfying the equation.

hence option 1 is correct.