In the regression model ŷ = a + bx, a and b are the:
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- In a simple regression problem, r and B O may have opposite signs. O must have the same sign. O must have opposite signs. O are equal.A real estate company wanted to see the relationship between home prices and square footage of homes for sale. The regression line is ŷ = –802,456 + 144x, where x is the square footage of a home. Complete the statement based on the information. For every -square-foot increase, the predicted home price is predicted to increase by $you take a bar of soap and weigh it after each shower. will the regression line be positive or negative
- A set of data consists of the number of years that applicants for Foreign Service jobs have studied German and the grades that they received on a proficiency test. The following regression equation is obtained: y-hat = 31.6 + 10.9x, where x is the number of years of study and y is the grade on the test. Identify the predictor and response variables. a. The number of years of study is our predictor variable; the scores on the test are our dependent variable. b. Not enough information is provided to determine c. Who cares? d. The scores on the test are our predictor variable; the number of years of study is our dependent variable.The following data show the brand, price ($), 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 ý = 22.525 + 0.325x, where x = price ($) and y overall score. %3D Brand Price ($) Score 180 78 B. 150 71 C 95 59 70 54 E 70 40 35 28 (a) Compute SST, SSR, and SSE. (Round your answers to three decimal places.) SST SSR %3D SSE = (b) Compute the coefficient of determination . (Round your answer to three decimal places.) 1 = Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) O The least squares line provided a good fit as a large proportion of the variability in y has been explained by the least squares line. O The least squares line did not provide a good fit as a large proportion of the variability in y…In a study, the simple linear regression equation was found as y = 3.02 - 10.30 * x. Accordingly, if the value of x is 7.74, what will be the value of "y"? 34 - O A) -82,74 O B) 45,74 O C) 76,70 O D) -76,70 O E) 24,43
- I need help with question 7, 8 and 9 plz.The scatterplot below shows Olympic gold medal performances in the long jump from 1900 to 1988. The long jump is measured in meters. Use the regression line to predict the average predicted long jump distance in 1950. A. The average predicted long jump distance in 1950 is 7.94 meters. B. The average predicted long jump distance in 1950 is 362.7 meters. C. The average predicted long jump distance in 1950 is 3,054 meters. D. The average predicted long jump distance in 1950 is 6.893 meters.A marketing consultant created a linear regression model to predict the number of units sold by a client based on the amount of money spent on marketing by the client. Which of the following is the best graphic to use to evaluate the appropriateness of the model?
- A linear regression model has three features: x1, x2, x3. The t-stat value for each feature is -150, 110, -70, respectively. You want to build a simpler model by deleting one of the features, from your dataset. Which feature you can safely remove from the data? a. Cannot decide b. x3 c. x2 d. x1The 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 ($) Score A 180 76 B 150 71 C 95 63 D 70 56 E 70 40 F 35 24 #1) Compute SST, SSR, and SSE. (Round your answers to three decimal places.) SST = SSR = SSE = #2) Compute the coefficient of determination r2.(Round your answer to three decimal places.) r2 = #2a) Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) A) The least squares line provided a good fit as a small proportion of the variability in y has been explained by the least squares line. B) The least squares line provided a good fit as a large…The following data show the brand, price ($), 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 = 21.592 + 0.324x, where x = price ($) and y = overall score. Brand Price ($) Score A 180 76 B 150 69 C 95 61 D 70 56 E 70 38 F 35 24 (a) Compute SST, SSR, and SSE. (Round your answers to three decimal places.) (b) Compute the coefficient of determination r2. (Round your answer to three decimal places.) (c) What is the value of the sample correlation coefficient? (Round your answer to three decimal places.)