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

there are no short passages to look at

you have orange juice on wednesday. (idk why this is the answer)

step-by-step explanation: