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please assist with non graded problem
The given information is
The regression model is
y = 17.5 + 3.5 x1 -2.5x2 + 7.4x3 + 2.9 x4
SST = 1800
SSR = 1764
n : Number of obervations = 30
k: Number of variables = 4
It is asked to compute
- R2
- Ra2
- Comment on the goodness of fit
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- The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.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 is based on 30 observations. y=17.4 - 4.0x 1- 2.3x2 +7.3x32.9x4 The values of SST and SSR are 1,808 and 1,760, respectively. Compute R2 (to 3 decimals). Compute Ra2 (to 3 decimals). How good is the fit provided by the estimated regression equation?
- The following table displays the mathematics test scores for a random sample of college students, along with their final SY16C grades. a. Fit the regression line y = a+bx to the data and interpret the results. b. Use the regression equation to determine the SY16C grade for a college student who scored60 on their achievement test. What would their SY16C grade be?From 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.The following estimated regression equation is based on 30 observations. ŷ = 18.3 + 3.9x1 − 2.2x2 + 7.5x3 + 2.5x4 The values of SST and SSR are 1,805 and 1,762, respectively. a. Compute R2 = (to 3 decimals). b. Compute Ra2 = (to 3 decimals).
- Which of the following does not need to be computed to determine a simple regression line? SSx SP "Y-hat" SSyThe 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 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 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…Consider the set of ordered pairs shown below. Assuming that the regression equation is y= 2.814 + 0.406x and the SSE = 5.313, construct a 90% prediction interval for x= 3. x 6 0 4 4 4 2 y 5 3 6 5 3 3 Calculate the upper and lower limits of the prediction interval. UPL=LPL= Someone please help me solve this! Thank you!The following multiple regression printout can be used to predict a person's average annual salary given his or her years of employment and number of years of education beyond high school. Regression Analysis: Salary Versus YrsEm, Educ Coefficients Term Coef SE Coef T-Value P-Value Constant 23,175 1,771 13.09 0.000 YrsEm 671 141 4.76 0.000 Educ 1,911 378 5.06 0.000 (a) Is the regression coefficient of education (Educ) statistically significant? (Use ? = 0.05.) Given this output, the regression coefficient for education (is/is not) statistically significant. (b) Does the variable education belong in the model? Given this output, the variable education (may/may not) belong in the model. (c) Given this output, which of the following is the correct interpretation for Education in this model? -For each additional year of education beyond high school, the estimated change in the average annual salary is $23,175, controlling for years of employment. -For each…