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, X, = amount ofski trail grooming, X3 = safety patrol visibility, and X4 = friendliness of guest services.PredictorInterceptLiftWaitAmountGroomedSkiPatrolVisibilityFriendlinessHostsCoefficient2.81070.15480.25560.0652-0.1204(a) Write the fitted regression equation. (Round your answers to 4 decimal places. Negative values should be indicated by a minussign.)ý =* LiftWait +* AmountGroomed +* SkiPatrolVisibility +* FriendlinessHosts(b) Interpret each coefficient.Overall satisfaction (Click to select) vwith an increase in satisfaction for each individual predictor except for friendliness of hosts.(c) Would the intercept seem to have meaning in this regression?O YesO No (d) Make a prediction for Overall Satisfaction when a guest's satisfaction in all four areas is rated a 3. (Round your answer to 4decimal places.)Overall satisfaction score

Answered: Image /qna-images/answer/553dd379-7c3b-4ccb-b613-8b5eb9b1b8f7.jpg

Answered: A ski resort asked a random sample of…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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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 Coefficient Intercept 2.9833 LiftWait 0.1458 AmountGroomed 0.2562 SkiPatrolVisibility 0.0428 FriendlinessHosts −0.1298 (a) Write the fitted regression equation. (Round your answers to 4 decimal places. Negative values should be indicated by a minus sign.) yˆy^ = + * LiftWait + * AmountGroomed + * SkiPatrolVisibility + * FriendlinessHosts (b) Interpret each coefficient. Overall satisfaction increases with an increase in satisfaction for each individual predictor except for friendliness of hosts. (d) Make a prediction for Overall Satisfaction when a guest’s satisfaction in…
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 45 people, calculate the tcalc 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 t-values to 3 decimal places and p- values to 4 decimal places.) Predictor Intercept AgeMed Coefficient SE tcalc p-value 4,641.0430 798.0634 -28.8630 12.4684 Bankrupt 20.1604 12.1079 FedSpend HSGrad% -0.0181 0.0181 -30.3196 7.1136 (b-1) What is the critical value of Student's tin Appendix D for a two-tailed test at a = .01? (Round your answer to 3 decimal places.) -value =
A real estate builder wishes to determine how house size (House) is influenced by family income (Income) and family size (Size). House size is measured in meter square and income is measured in IDR millions. The builder randomly selected 50 families and ran the multiple regression. Partial Microsoft Excel output is provided below: Which of the independent variables in the model are significant at the 5% level? Formulate the hypothesis and explain the answer. How far can you rely upon this model? Or, what is the percentage variation in House explained by the model? What is the predicted house size (in hundreds of square feet) for an individual earning an annual income of IDR 400 million and having a family size of 4?
As part of a study designed to compare hybrid and similarly equipped conventional vehicles, Consumer Reports tested a variety of classes of hybrid and all-gas model cars and sport utility vehicles (SUV’s). You are given the required information in the Excel data-file named HybridTest. Test for any significant effect due to Class, Type using multiple regressions. Create dummy variables for Class and Type. Use alpha=0.05 Make/Model Class Type MPG Honda Civic Small Car Hybrid 37 Honda Civic Small Car Conventional 28 Toyota Prius Small Car Hybrid 44 Toyota Corolla Small Car Conventional 32 Chevrolet Malibu Midsize Car Hybrid 27 Chevrolet Malibu Midsize Car Conventional 23 Nissan Altima Midsize Car Hybrid 32 Nissan Altima Midsize Car Conventional 25 Ford Escape Small SUV Hybrid 27 Ford Escape Small SUV Conventional 21 Saturn Vue Small SUV Hybrid 28 Saturn Vue Small SUV Conventional 22 Lexus RX Midsize SUV Hybrid 23 Lexus RX Midsize SUV Conventional 19…
If the regression line is not a "good fit" what would be better to use to approximate a response variable?
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
A researcher investigates the relationship between study habits and college achievement. College seniors were administered the Inventory of Study Habits Survey (X) to measure study habits and the College BASE (Y) was used to measure overall college achievement. The correlation between the study habits and achievement was found to be 0.784. The researcher concluded that students with higher scores on the Study Habits Survey will always have higher college achievement scores on the College BASE. Is the researcher's conclusion correct? Why or why not?
You are analyzing a dataset containing 379 datapoints, and want to use 13 predictor variables to create a multiple variable linear regression model of the data. You conduct an ANOVA analysis, and yield a R² of 38%. Using this information, what would be the F statistic of your analysis?
You plan to fit a regression model that will be used to predict first-year college GPA (FYGPA) from high-school GPA (HSGPA), ACT score (ACT), first-generation status (Yes or No), socioeconomic class (lower class, lower to middle class, middle to upper class, and upper class), and school type (public or private). What is the total number of estimated regression coefficients? If the sample size is n = 250 students, what are the degrees of freedom for the following sources of variation: Regression Error Total
The local utility company surveys 12 randomly selected customers. For each survey participant, the company collects the following: annual electric bill (in dollars) and home size (in square feet). Output from a regression analysis appears below: Bill 13.45 + 4.39*Size Coefficients Estimate Std. Error (Intercept) 13.45 Size 4.39 0.54 0.2 We are 90% confident that the mean annual electric bill increases by between dollars and dollars for every additional square foot in home size. Round your answers to three decimal places and enter in increasing order.
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.)
The value of PRESS for five different regression models are A = 42.3, B = 47.4, C = 51.5, D =40.6, and E = 54.6. Based only on this statistic, which model is preferred?

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