Given are five observations for two variables, x and y.5151720Yi5153431712Use the estimated regression equation: ŷ = 62.5684 – 2.2807a.a. Compute the mean square error using equation.SSE82 = MSE- 2(to 4 decimals)b. Compute the standard error of the estimate using equation.SSEs = VMŞEn- 2(to 4 decimals)c. Compute the estimated standard deviation of b1 using equation.VE (2i – 7)?(to 4 decimals)d. Use the t-test to test the following hypotheses (a = 0.10):Ho: B1 = 0Ha: B1 +0Compute the value of the t-test statistic (Enter negative values as negative numbers).(to 3 decimals)3.

The given regression equation is y^=62.5684-2.2807x.

Answered: Given are five observations for two…

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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4.For a sample of 12 observations, a businessman wants to regress the price (in dollar) of the laptop (Y) on the processor's speed (X). The summary results of the observations are given below. Σx = 19.8 , Σy = 24798, Σxy = 431882 Σx^2 = 33.88, Σγ^2 = 57365692 (b)Find the fitted regression line of the price of laptop on processor speed. (c) Find the predicted price of the laptop (y) for the processor speed x-1.9. (d) Compute the coefficient of determination and comment.
Ten observations were provided for a dependent variable y and two independent variables x1 and x2; for these data, SST = 15,177.6 and SSR = 14,059.3. (a) Compute R2. (Round your answer to three decimal places.) R2 = (b) Compute Ra2. (Round your answer to three decimal places.) Ra2 = (c) Does the estimated regression equation explain a large amount of the variability in the data? Explain. (For purposes of this exercise, consider an amount large if it is at least 55%. Round your answer to one decimal place.) , after adjusting for the number of independent variables in the model, we see that % of the variability in y has been accounted for.
Ten observations were provided for a dependent variable y and two independent variables x1 and x2; for these data, SST = 15,177.6 and SSR = 14,056.5. (a) Compute R2. (Round your answer to three decimal places.) R2 = (b)Compute Ra2.( Round your answer to three decimal places.) Ra2 = (c)Does the estimated regression equation explain a large amount of the variability in the data? Explain. (For purposes of this exercise, consider an amount large if it is at least 55%. Round your answer to one decimal place.) (Select Yes OR No) after adjusting for the number of independent variables in the model, we see that ______% of the variability in y has been accounted for.
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 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.
A set of n = 15 pairs of X and Y values has a correlation of r = +0.80 with SSY = 75, and the regression equation for predicting Y is computed. Find the standard error of estimate for the regression equation. How big would the standard error be if the sample size were n = 30.
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.
Use the following set of points to test the null hypothesis =:H0β10 versus <:H1β10 . Use the P -value method with the =α0.10 level of significance. The slope of the regression line for this data is computed to be =b1−0.46482 , and the standard error of b1 is computed as =sb0.256636 . Use the TI- 84 calculator. x 14 14 4 16 21 14 15 9 y 17 14 19 9 10 10 9 10 t-score= p-value=
If the standard error of the estimate for a regression model fitted to a large number of paired observations is 1.75, approximately 95% of the residuals would lie within ______. −3.50 and +3.50 −1.75 and +1.75 −0.95 and +0.95 −0.68 and +0.68 −0.97 and +0.97
Consider a linear regression model for the decrease in blood pressure (mmHg) over a four-week period with muy=2.8+0.8x and standard deviation chi=3.2. The explanatory variable x is the number of servings fruits and vegetables in a calorie-controlled diet. Using the 68-95-99.7 rule, between what two values would approximately 95% of the observed responses, y, fall when x = 7?
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…

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