With reference to the following data, find the correlation coefficient and the regression equation for the values of 7 over the values of . the following questions: 91 87 58 63 75 66 50 34 68 71 79 80 Q7/ \% x over 7 that the regression line equation is -
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- Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4The following estimated regression equation based on 10 observations was presented. ŷ = 29.1260 + 0.5306x1 + 0.4680x2 The values of SST and SSR are 6,728.125 and 6,215.375, respectively. (a) Find SSE. SSE = (b) Compute R2. (Round your answer to three decimal places.) R2 = (c) Compute Ra2. (Round your answer to three decimal places.) Ra2 = (d) Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) The estimated regression equation provided a good fit as a small proportion of the variability in y has been explained by the estimated regression equation.The estimated regression equation did not provide a good fit as a small proportion of the variability in y has been explained by the estimated regression equation. The estimated regression equation provided a good fit as a large proportion of the variability in y has been explained by the estimated regression equation.The following estimated regression model was developed relating yearly income (y in $1000s) of 30 individuals with their age (x1) and their gender (x2) (0 if male and 1 if female).ŷ = 30 + 0.7x1 + 3x2Also provided are SST = 1200 and SSE = 384.The multiple coefficient of determination is _____.
- The following estimated regression equation based on 30 observations was presented. ŷ = 17.6 + 3.8x1 − 2.3x2 + 7.6x3 + 2.7x4 The values of SST and SSR are 1,808 and 1,780, respectively. (a) Compute R2. (b) Compute Ra2. (c) Comment on the goodness of fit.The following estimated regression equation based on 30 observations was presented. ŷ = 17.6 + 3.8x1 − 2.3x2 + 7.6x3 + 2.7x4 The values of SST and SSR are 1,807 and 1,757, respectively. (a) Compute R2. (Round your answer to three decimal places.) R2 = (b) Compute Ra2. (Round your answer to three decimal places.) Ra2 = (c) Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) The estimated regression equation did not provide a good fit as a large proportion of the variability in y has been explained by the estimated regression equation. The estimated regression equation provided a good fit as a large proportion of the variability in y has been explained by the estimated regression equation. The estimated regression equation provided a good fit as a small proportion of the variability in y has been explained by the estimated regression equation. The estimated regression equation did not provide a good…The following estimated regression equation based on 30 observations was presented. ŷ = 17.6 + 3.8x1 − 2.3x2 + 7.6x3 + 2.7x4 The values of SST and SSR are 1,801 and 1,758, respectively. (a)Compute R2. (Round your answer to three decimal places.) R2 = (b)Compute Ra2.(Round your answer to three decimal places.) Ra2 = (c) Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) The estimated regression equation provided a good fit as a small proportion of the variability in y has been explained by the estimated regression equation.The estimated regression equation did not provide a good fit as a large proportion of the variability in y has been explained by the estimated regression equation. The estimated regression equation did not provide a good fit as a small proportion of the variability in y has been explained by the estimated regression equation.The estimated regression equation provided a good fit as a…
- The following estimated regression model was developed relating yearly income (y in $1000s) of 30 individuals with their age (x1) and their gender (x2) (0 if male and 1 if female).ŷ = 30 + 0.7x1 + 3x2Also provided are SST = 1200 and SSE = 384.The yearly income of a 24-year-old female individual is _____.Consider the multiple regression for the following experiment: yi=b0+b1x1i+b2x2i+b3x3i+ei Where yi is the number of touchdowns, x1i is rushing yards, x2i is passing yards, and x3i is the “time of possession of the football” in minutes for that football team. Which of the following statements is true when making an interpretation of the sample slope coefficient? a) a. b2 represents the marginal change in passing yards for every additional touchdown, holding the other variables constant b) b. b2 represents the marginal change in touchdowns for every additional passing yard, holding the other variables constant c) c. b1 represents the marginal change in touchdowns for every additional passing yard, holding the other variables constant d) d. b3 represents the marginal change in touchdowns for every additional minute of time of possession, holding touchdowns constantIn a regression analysis involving 27 observations, the following estimated regressionequation was developed:yˆ 5 25.2 1 5.5x1For this estimated regression equation SST = 1550 and SSE = 520.a. At a = .05, test whether x1 is significant.Suppose that variables x2 and x3 are added to the model and the following regressionequation is obtained.yˆ 5 16.3 1 2.3x1 1 12.1x2 2 5.8x3For this estimated regression equation SST = 1550 and SSE = 100.
- The following estimated regression equation is based on 10 observations was presented. ŷ = 29.1270 + 0.5906x1 + 0.4980x2 . Here SST=6,724.125 , SSR = 6,216.375 , sb1 = 0.0813, sb2 = 0.0567. Compute MSR & MSE to 3 decimals, then compute F using the appropriate F test (round answer to 3 decimals). Use α = 0.05.Which of the following does not need to be computed to determine a simple regression line? SSx SP "Y-hat" SSyFrom the following data, determine if the data has a positive or a negative relationship with each other. Showcase the regression line, and determine if the data provided fits the approximate curve. Use the formula attached together with the given data.