Answer part B using information from part a! b.Use part (a) to perform the F test [show the formula used to calculate F-statisticvalue] for testing the significance of the straight-line model (Use a = 0.10). Interpret yourdecision. Edited SAS Output (PROC REG) for Problem 6a.Regression of ATST (Y) on AGE (X)Root MSEVariableInterceptX[Portion of output omitted]DF1113.15238 R-SquarePARAMETER ESTIMATESStandardErrorParameterEstimate646.48334-14.04105Assume that n = 13, S₁x = 172.985, and SSY = 20,123.382.0.905412.917731.36812Construct the ANOVA table for regression of ATST on AGE.t Value50.05-10.26

Answered: Image /qna-images/answer/3506f029-a9f0-4652-98e3-f20cd5a19e28.jpg

Answered: b. Use part (a) to perform the F test…

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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2. You estimated a regression with the following output. Source | SS df MS Number of obs = 332 -------------+---------------------------------- F(1, 330) = 2.32 Model | 71599.1822 1 71599.1822 Prob > F = 0.1284 Residual | 10170207.7 330 30818.8111 R-squared = 0.0070 -------------+---------------------------------- Adj R-squared = 0.0040 Total | 10241806.9 331 30942.0147 Root MSE = 175.55 ------------------------------------------------------------------------------ Y | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- X | .7575183 .4969893 1.52 0.128 -.2201484 1.735185 _cons | 28.87757 42.80371 0.67 0.500 -55.32498 113.0801…
Although the Excel regression output, shown in Figure 12.21 for Demonstration Problem 12.1, is somewhat different from the Minitab output, the same essential regression features are present. The regression equation is found under Coefficients at the bottom of ANOVA. The slope or coefficient of x is 2.2315 and the y-intercept is 30.9125. The standard error of the estimate for the hospital problem is given as the fourth statistic under Regression Statistics at the top of the output, Standard Error = 15.6491. The r2 value is given as 0.886 on the second line. The t test for the slope is found under t Stat near the bottom of the ANOVA section on the “Number of Beds” (x variable) row, t = 8.83. Adjacent to the t Stat is the p-value, which is the probability of the t statistic occurring by chance if the null hypothesis is true. For this slope, the probability shown is 0.000005. The ANOVA table is in the middle of the output with the F value having the same probability as the t statistic,…
You estimated a regression with the following output. Source | SS df MS Number of obs = 425 -------------+---------------------------------- F(1, 423) > 99999.00 Model | 1.2222e+09 1 1.2222e+09 Prob > F = 0.0000 Residual | 3629692.46 423 8580.83324 R-squared = 0.9970 -------------+---------------------------------- Adj R-squared = 0.9970 Total | 1.2258e+09 424 2891064.27 Root MSE = 92.633 ------------------------------------------------------------------------------ Y | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- X | 28.30715 .0750055 377.40 0.000 28.15972 28.45458 _cons | 64.92678 7.590905 8.55 0.000 50.00619 79.84738…
You estimated a regression with the following output. Source | SS df MS Number of obs = 398 -------------+---------------------------------- F(1, 396) > 99999.00 Model | 7.5632e+09 1 7.5632e+09 Prob > F = 0.0000 Residual | 2035000.94 396 5138.89127 R-squared = 0.9997 -------------+---------------------------------- Adj R-squared = 0.9997 Total | 7.5652e+09 397 19056009.8 Root MSE = 71.686 ------------------------------------------------------------------------------ Y | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- X | 45.36043 .0373903 1213.16 0.000 45.28692 45.43394 _cons | 50.3265 4.38097 11.49 0.000 41.71363 58.93937…
A set of n=20 pairs of x and y scores had SSx=10,SSy=40,and SP=30.What is the slope for the regression equation for predicting y from x?
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. What is the slope of the population regression line?
A set of n=15 pairs of x and y scores has sx=10, ssy=40, and sp=30. What is the slope for the regression for predicting y from x?
You estimated the following regression. What value would you predict for Y, if X = 56? (Round your final answer to zero decimal places.) Source | SS df MS Number of obs = 196 -------------+---- F(1, 194) > 99999.00 Model | 923620205 1 923620205 Prob > F = 0.0000 Residual | 931949.999 194 4803.86597 R-squared = 0.9990 -------------+------ Adj R-squared = 0.9990 Total | 924552155 195 4741293.1 Root MSE = 69.31 ------------------------------------------------------------------------------ Y | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- X | 42.80034 .0976104 438.48 0.000 42.60782 42.99285 _cons | 81.67896 7.821598 10.44 0.000 66.25268 97.10525…
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. What is the subpopulation mean when x = 7 servings per day?
The Tiliche Corp. analyst conducted 10 independent timing studies in the manual spray painting section of the finishing department. The product line under study revealed a direct relationship between spray painting time and product surface area. The following data were collected (ignore the qualification factor): (image) a) Find the linear model relating standard time (y) to surface area (x) using linear regression.(x) using linear regression.b) How much time would you allocate to spray painting a new part with a surface area of 250 in2?surface area of 250 in2?c) Obtain the fitted value of y and the corresponding residual for a particular assembly (study #3), with a surface area of 250 inches2?(study #3), with an area of 150 square inches.d) Perform a significance test of the regression using α= 0.05. Find the P-value for this test.What are your conclusions?e) Estimate the standard errors of the slope and the value of the intercept.f) Calculate the coefficient of determination R2 .g)…
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?
What would be the simple linear regression (trend projection) forecast for week 4 and for week 53 for Small Town Restaurant (see file) if the regression equation for our data is: y = 3061.7 + 0.2364x ? Provide two decimal places and use normal rounding.

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b. Use part (a) to perform the F test [show the formula used to calculate F-statistic value] for testing the significance of the straight-line model (Use a = 0.10). Interpret your decision.