Chapter 12, Problem 12.8AC

HOW DO YOU SEE IT? Discuss how well a linear model approximates the data shown in each scatter plot.

Demand for Candy Bars In this problem you will determine a linear demand equation that describes the demand for candy bars in your class. Survey your classmates to determine what price they would be willing to pay for a candy bar. Your survey form might look like the sample to the left. a Make a table of the number of respondents who answered yes at each price level. b Make a scatter plot of your data. c Find and graph the regression line y=mp+b, which gives the number of respondents y who would buy a candy bar if the price were p cents. This is the demand equation. Why is the slope m negative? d What is the p-intercept of the demand equation? What does this intercept tell you about pricing candy bars? Would you buy a candy bar from the vending machine in the hallway if the price is as indicated. Price Yes or No 50 75 1.00 1.25 1.50 1.75 2.00

What is interpolation when using a linear model?

A magazine publishes restaurant ratings for various locations around the world. The magazine rates the restaurants for food, decor, service, and the cost per person. Develop a regression model to predict the cost per person, based on a variable that represents the sum of the three ratings. The magazine has compiled the accompanying table of this summated ratings variable and the cost per person for 25 restaurants in a major city. Complete parts (a) through (e) below. Click the icon to view the table of summated ratings and cost per person. ..... a. Construct a scatter plot. Choose the correct graph below. A. Ов. С. D. ACost ($) 90- ACost ($) 90- ACost ($) 90- ACost ($) 90- 0- 0- 90 90 90 90 Rating Rating Rating Rating b. Assuming a linear relationship, use the least-squares method to compute the regression coefficients b, and b,. bo = and b, (Round to two decimal places as needed.) c. Interpret the meaning of the Y-intercept, bo, and the slope, b,. Choose the correct answer below. O A.…

A magazine publishes restaurant ratings for various locations around the world. The magazine rates the restaurants for food, decor, service, and the cost per person. Develop a regression model to predict the cost per person, based on a variable that represents the sum of the three ratings. The magazine has compiled the accompanying table of this summated ratings variable and the cost per person for 25 restaurants in a major city. Complete parts (a) through (e) below. Click the icon to view the table of summated ratings and cost per person. a. Construct a scatter plot. Choose the correct graph below. O A. Ов. OC. OD. ACost ($) 90- Q A Cost ($) 904 A Cost ($) 90- ACost ($) 90- 0- 0- 0- 0- 90 Rating 90 Rating 90 90 Rating Rating Summated ratings and cost per person b. Assuming a linear relationship, use the least-squares method to compute the regression coefficients bo and b,. bo =D and b, =O (Round to two decimal places as needed.) Summated Rating Cost ($ per person)|9 c. Interpret the…

A magazine publishes restaurant ratings for various locations around the world. The magazine rates the restaurants for food, decor, service, and the cost per person. Develop a regression model to predict the cost per person, based on a variable that represents the sum of the three ratings. The magazine has compiled the accompanying table of this summated ratings variable and the cost per person for 25 restaurants in a major city. Complete parts (a) through (e) below. Click the icon to view the table of summated ratings and cost per person. a. Construct a scatter plot. Choose the correct graph below. O A. 90+ 0 0 Cost ($) The M Rating 90 Q O B. A Cost (5) 90+ 0 H +4 Alpe Rating 90 Q b. Assuming a linear relationship, use the least-squares method to compute the regression coefficients bo and b₁. bo= and b₁ = (Round to two decimal places as needed.) C O C. 90+ 0- Cost (S) HA Rating 90 Q Summated Ratings and Cost Per Person Summated Rating Cost ($ per person) 40 48 60 61 42 40 43 55 67 69…

A FIFA World Cup football is dropped from 35 different heights (in cm) and the height of the bounce is recorded (in cm.) The regression analysis gives the model bounce = -0.1 +0.70 drop. Predict the height of the bounce if dropped from 64 cm. 44.7 cm 44.8 cm 64.6 cm 91.57 cm 44.9 cm

you take a bar of soap and weigh it after each shower.  will the regression line be positive or negative

The value of a sports franchise is directly related to the amount of revenue that a franchise can generate. Below is the data that represents the value (in $millions) and the annual revenue (in $millions) for 30 Major League Baseball franchises. Suppose you want to develop a simple linear regression model to predict franchise value based on annual revenue generated.     Team Revenue Value Baltimore 179 460 Boston 310 1000 Chicago White Sox 214 600 Cleveland 178 410 Detroit 217 478 Kansas City 161 354 Los Angeles Angels 226 656 Minnesota 213 510 New York Yankees 439 1850 Oakland 160 321 Seattle 210 585 Tampa Bay 161 323 Texas 233 674 Toronto 188 413 Arizona 186 447 Atlanta 203 508 Chicago Cubs 266 879 Cincinnati 185 424 Colorado 193 464 Houston 196 549 Los Angeles 230 1400 Miami 148 450 Milwaukee 195…