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. OB. OC. OD. Cost (5) 90- Cost ($) 90- ACost ($) 90- Cost ($) 90- 0- 0- 0- 0- 90 90 90 90 Rating Rating Rating Rating

Mary used a sample of 68 large U.S. cities to estimate the relationship between Crime (annual property crimes per 100,000 persons) and Income (median annual income per capita, in dollars). Her estimated regression equation was Crime = 428 + 0.050 Income. If Income decreases by 500, we would expect that Crime will Group of answer choices remain unchanged. decrease by 25. increase by 500. decrease by 50.

$339,380 $41,768 A national homebuilder builds single-family homes and condominium-style townhouses. The accompanying dataset provides information on the selling price, lot cost, and type of home for closings during one month. Complete parts a through c. E Click the icon to view the house sales data a. Develop a multiple regression model for sales price as a function of lot cost and type of home without any interaction term. Create a dummy variable named "Townhouse", where it is equal to 1 when Type = "Townhouse" and 0 otherwise. Determine the coefficients of the regression equation. Sales Price = 108726 + (3.68 ) • Lot Cost + ( - 75063 )• Townhouse (Round the constant and coefficient of Townhouse to the nearest integer as needed. Round all other values to two decimal places as needed.) b. Determine if an interaction exists between lot cost and type of home and find the best model. Use a = 0.1 as the level of significance. First determine whether an interaction exists. Select the…

please assist with this non graded assisnment. A tutor provided me with incorrect answers so I am resubmitting my question.

The table contains price-supply data and   price-demand data for corn. Find a linear regression model for the price-supply data where x is supply​ (in billions of​ bushels) and y is price​ (in dollars). Do the same for the price-demand data. Find the equilibrium price for corn.   Price ($/bu) Supply (billion bu) Price ($/bu) Demand (billion bu) 2.14 6.41 2.06 9.96 2.25 7.38 2.15 9.42 2.34 7.51 2.26 8.33 2.41 7.78 2.32 8.08 2.46 8.13 2.36 7.86 2.57 8.35 2.48 6.96   ...   Question content area right Part 1 Find a linear regression model for the price-supply data where x is supply​ (in billions of​bushels) and y is price​ (in dollars).   y=enter your response here ​(Type an equation using x as the variable. Round to two decimal places as​ needed.)

The arm span and foot length were both measured (in centimeters) for each of 20 students in a biology class. The computer output displays the regression analysis.   Which of the following is the best interpretation of the coefficient of determination r2? About 37% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 65% of the variation in foot length is accounted for by the linear relationship formed with the arm span. About 63% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 63% of the variation in foot length is accounted for by the linear relationship formed with the arm span.

The following data show the brand, price ($), and the overall score for six stereo headphones that were tested by a certain magazine. The overall score is based on sound quality and effectiveness of ambient noise reduction. Scores range from 0 (lowest) to 100 (highest). The estimated regression equation for these data is ŷ = 22.391 + 0.326x, where x = price ($) and y = overall score. Brand Price ($) Score A 180 76 B 150 71 C 95 63 D 70 56 E 70 40 F 35 24   #1) Compute SST, SSR, and SSE. (Round your answers to three decimal places.) SST = SSR = SSE =   #2) Compute the coefficient of determination r2.(Round your answer to three decimal places.) r2 =   #2a) Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) A) The least squares line provided a good fit as a small proportion of the variability in y has been explained by the least squares line. B) The least squares line provided a good fit as a large…

Range of ankle motion is a contributing factor to falls among the elderly. Suppose a team of researchers is studying how compression hosiery, typical shoes, and medical shoes affect range of ankle motion. In particular, note the variables Barefoot and Footwear2. Barefoot represents a subject's range of ankle motion (in degrees) while barefoot, and Footwear2 represents their range of ankle motion (in degrees) while wearing medical shoes. Use this data and your preferred software to calculate the equation of the least-squares linear regression line to predict a subject's range of ankle motion while wearing medical shoes, ?̂ , based on their range of ankle motion while barefoot, ? . Round your coefficients to two decimal places of precision. ?̂  = A physical therapist determines that her patient Jan has a range of ankle motion of 7.26°7.26° while barefoot. Predict Jan's range of ankle motion while wearing medical shoes, ?̂ . Round your answer to two decimal places. ?̂ = Suppose Jan's…

What's a good topic for a regression topic? Make sure you have two quantitative variables (for example # of siblings and heart rate). Ask for another variable like academic year, major, hobbies, favorite genre of movie. - State the independent and dependent variables and what is the population.

A multiple regression analysis has more than onea. Fixed costsb. Dependent variablec. independent variabled. both fixed costs and dependent variable