A ski resort asked a random sample of guests to rate their satisfaction on various attributes of their visit on a scale of 1-5 with 1= veryunsatisfied and 5 = very satisfied. The estimated regression model was Y= overall satisfaction score, X = lift line wait, X2 = amount ofski trail grooming, X3 = safety patrol visibility, and X4 = friendliness of guest services.PredictorCoefficient2.9018InterceptLiftwait0.1642AmountGroomed0.2343SkiPatrolVisibilityFriendlinessHosts0.0602-0.1193(a) Write the fitted regression equation. (Round your answers to 4 decimal places. Negative values should be indicated by a minussign.)* LiftWait +* AmountGroomed +SkiPatrolVisibility +|* FriendlinessHosts(b) Interpret each coefficient.Overall satisfaction Click to select)with an increase in satisfaction for each individual predictor except for friendliness of hosts.(c) Would the intercept seem to have meaning in this regression?YesNo(d) Make a prediction for OverallI Satisfaction when a guest's satisfaction in all four areas is rated a 3. (Round your answer to 4decimal places.)Overall satisfaction score

Note: Hey, since multiple subparts are posted, we will answer first three subparts according to our…

Answered: A ski resort asked a random sample of…

College Algebra

1st Edition

ISBN:9781938168383

Author:Jay Abramson

Publisher:Jay Abramson

Chapter4: Linear Functions

Section: Chapter Questions

Problem 30PT: For the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or...

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Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
For the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or older who are college graduates in a particular city, by year. Based on the set of data given in Table 5, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient. Round to three decimal places of accuracy
A ski resort asked a random sample of guests to rate their satisfaction on various attributes of their visit on a scale of 1-5 with 1 = very unsatisfied and 5 = very satisfied. The estimated regression model was Y=overall satisfaction score, X₁ = lift line wait, X₂ = amount of ski trail grooming, X3 = safety patrol visibility, and X4 = friendliness of guest services. Predictor Intercept LiftWait AmountGroomed SkiPatrolVisibility FriendlinessHosts (a) Write the fitted regression equation. (Round your answers to 4 decimal places. Negative values should be indicated by a minus sign.) |ŷ = + (b) Interpret each coefficient. Overall satisfaction Coefficient 2.9233 0.1544 0.2403 0.0645 -0.1291 LiftWait + *AmountGroomed + with an increase in satisfaction for each individual predictor except for friendliness of hosts. * SkiPatrolVisibility + * FriendlinessHosts
Five pairs of data are used in determining a regression line ŷ = -3 + 4x. If the five values of the explanatory variable are 28, 45, 16, 41, and 20, respectively, what is the mean of the five values of the response variable?
A car lot wants to predict the # of car accessories they need to sell monthly based on the number of cars sold. The car lot owner randomly selects 12 months of data. The simple linear regression equation is ý = 14 - 2x. The coefficient of determination is 0.6364. What is the correlation coefficient to describe the relationship between these two variables? Multiple Choice
he average height of a large group of children is 43 inches, and the SD is 1.2 inches. The average weight of these children is 40 pounds, and the SD is 2pounds. The correlation between the two variables is r = 0.65.A scatter diagram is drawn, with height on the horizontal axis and weight on the vertical axis. The scatter diagram is football-shaped. The regression line forpredicting weight based on height is drawn through the scatter.Q. Predict the weights and the typical size of the error for those predictions ineach of the following case: Suppose a child’s height is at the 29th percentile of all heights. Using regression, our best guess is that the child’s weight (measured in pounds) is at the___________________ percentile compared to all other children.
Zagat’s publishes restaurant ratings for various locations in the United States. The following table contains the Zagat rating for food, décor, service, and the cost per person for a sample of 100 restaurants located in New York City and in a suburb of New York City. Develop a regression model to predict the cost per person, based on a variable that represents the sum of the ratings for food, décor, and service. Predict the mean cost per person for a restaurant with a sum-mated rating of 50. What should you tell the owner of a group of restaurants in this geographical area about the relationship between the summated rating and the cost of a meal? Location Food Décor Service Summated Rating Coded Location Cost Bins Midpoints City 22 14 19 55 0 33 19.99 25 City 20 15 20 55 0 26 29.99 35 City 23 19 21 63 0 43 39.99 45 City 19 18 18 55 0 32 49.99 55 City 24 16 18 58 0 44 59.99 65 City 22 22 21 65 0 44 69.99 75 City 22 20 20 62 0 50 79.99 85 City 20 19…
D& T LTD marketing team needed more information about the effectiveness of their 3 main mode of advertising. To determine which type is the most effective, the manager collected one week’s data from 25 randomly selected stores. For each store, the following variables were recorded: Weekly gross sales Weekly expenditure on direct mailing (Direct) Weekly expenditure on newspaper advertising (Newspaper) Weekly expenditure on television commercials (Television) Following is the regression output based on the above-mentioned data. SUMMARY OUTPUT Regression Statistics Multiple R 0.442…
The general manager of an engineering firm wants to know whether a technical artist's experience influences the quality of his or her work. A random sample of 24 artists is selected and their years of work experience and quality rating (as assessed by their supervisors) recorded. Work experience (EXPER) is measured in years and quality rating (RATING) takes a value of 1 through 7, with 7 = excellent and 1 = poor. The simple regression model RATING = ẞ1 + ẞ₂EXPER+ € is proposed. The least squares estimates of the model, and the standard errors of the estimates, are RATING= 3.204 +0.076EXPER (se) (0.709) (0.044) (a) Interpret the coefficient of EXPER. (b) Construct a 95% confidence interval for B2, the slope of the relationship between quality rating and experience. In what are you 95% confident? (c) Test the null hypothesis that ẞ2 is zero against the alternative that it is not using a two-tail test and the α = 0.05 level of significance. What do you conclude? (d) Test the null…
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. Predict the mean cost per person for a restaurant with a summated rating of 70.
A car dealership would like to develop a regression model that would predict the number of cars sold per month by a dealership employee based on theemployee's number of years of sales experience. The accompanying regression output was developed based on a random sample of employees. a. Predict the sales next month for an employee with 2.5 years of experience. The predicted sales is 8.6 cars. b. Compute the coefficient of determination and interpret its meaning. The coefficient of determination is 0.234 Therefore, about _________% of the variation in monthly sales is explained by the years of sales experience. (Type an integer or decimal rounded to one decimal place as needed.)
A regression model to predict Y, the state burglary rate per 100,000 people, used the following four state predictors: X₁ = median age, X₂ = number of bankruptcies per 1.000 population, X3 = federal expenditures per capita (a leading predictor), and X4 = high school graduation percentage. Click here for the Excel Data File (a) Using the sample size of 50 people, calculate the calc and p-value in the table given below. (Negative values should be indicated by a minus sign. Leave no cells blank - be certain to enter "0" wherever required. Round your answers to 4 decimal places.) Predictor Intercept AgeMed Bankrupt FedSpend HSGrad% Answer is complete but not entirely correct. *calc 5.2526 -2.1764✔✔ 1.4101✔ Coefficient 4,198.5808 -27.3540 17.4893 -0.0124 -29.0314 SE 799.3395 12.5687 12.4033 0.0176 7.1268 -0.7045 -4.0736 p-value 0.0000 0.0348 0.2935 0.4848 0.0002

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