Consider the paired data:I1.42y4.114.2212.289.16 28.627.9224.829.5929.82EįFind estimates for the linear model y = Bo+812, +e, where ~ N(0,0²).That is find 3o. 31, à. Also perform a test of the null hypothesis Ho3₁ = 0 at level a = 0.01.

To find out the regression estimate, we need to perform Regression Analysis. For this we will use…

Answered: Consider the paired data: I 1.42 4.22…

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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Given are five observations for two variables, and y. The estimated regression equation for these data is = 75.74-2.92x. a. Compute SSE, SST, and SSR. Yi The least squares line provided an - Select your answer decimal). fit; 4 SSE (to 2 decimals) SST (to 2 decimals) SSR (to 2 decimals) b. Compute the coefficient of determination ². Comment on the goodness of fit. (to 3 decimals) 00 15 18 20 57 57 46 17 12 Check My Work (2 remaining) % of the variability in y has been explained by the estimated regression equation (to 1 c. Compute the sample correlation coefficient. Enter negative value as negative number. (to 3 decimals)
4. The following output from R presents the results from computing a linear model. In our data example we are interested to study the relationship between students' academic performance api00 with variable enroll which is the number of students in the school. Call: Im (formula = api00 enroll, data = d) Residuals: мin 10 Median 30 Маx -285.50 -112.55 -6.70 95.06 389.15 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 744.25141 15.93308 46.711 < 2e-16 *** enroll -0.19987 0.02985 -6.695 7.34e-11 *** --- Signif. codes: O ' *** ' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 135 on 398 degrees of freedom Multiple R-squared: 0.1012, Adjusted R-squared: F-statistic: 44.83 on 1 and 398 DF, p-value: 7.339e-11 0.09898
Q1. The values of X and Y are given in the following table. X0235 8. Y 157 11 | 17 = 18. Y = 41, xY 222, > x² = 102, > Yy² X = 485 a) Find the Coefficient of Correlation b) Find the Coefficient of Determination and Coefficient of Non-Determination? c) Calculate the line-of-best- t (linear regression line) Ý = a + bX, d) If x = 8, estimate the response y.
12
I need solutions for d) and e). Please.
4.3. Suggest a reasonable value for the biasing constant c based on the VIF values and R² using the following table. Motivate your suggestion. Also give the fitted model. с b b bR (VIF₂) (VIF₂) (VIF3) R² 0.01 0.51 0.32 0.16 10 10.5 2 0.81 0.02 0.50 0.33 0.16 9 8 1.9 0.805 0.04 0.52 0.33 0.15 8 7 1.7 0.8 0.05 0.57 0.34 0.15 5 4 1.3 0.80 0.06 0.55 0.352 0.145 2 2.5 1.01 0.795 0.07 0.545 0.352 0.145 1.1 1.05 0.98 0.8
In a one-way analysis of variance with three treatments, each with five measurements, in which a completely randomized design is used, what is the degrees of freedom for treatments? a. 5 b. 2 c. 4 d. 8
Consider the following data values for variables x and y: Ť 8 10 5 2 3 1 X 5 4 3 6 9 8 10 The regression coefficients were calculated as bo = 13.223 and b₁ = -1.257. Select the correct statement. Select one: O a. If x = 2, the estimated value of y from the regression line is -25.189. b. The least--squares regression line is y = 13.223-1.257x. c. An x-value of 11 resulted in an estimated y value of -1.861 d. The least--squares regression line is y = 1.257-13.223x. e. The relationship between x and y appears to be linear and positive.
Q2: For the raw data shown in Table below: 1) Find out which of the x₁ or x₂ variables is better correlated to y. 2) Find out the linear regression lines: y₁ = f(x₁) and y2 = f(x₂) depending on the results of 1) above. X1 1 3 4 11 14 X2 1 2 3 12 15 y 1 2 4 9 65 87 99 4 5 сл 7 12 8
Solve the following problems based on the step-by-step procedure of the Non-Parametric Tests. Show complete solutions and answer. When nicotine is absorbed by the body, cotinine is produced. A measurement of cotinine in the body is therefore a good indicator of how much a person smokes. Listed below are the reported numbers of cigarettes smoked per day and the measured amounts of nicotine (in ng/ml). Is there a significant correlation at alpha = 0.05? x (cigarettes/day) 60 10 4 15 10 1 20 8 7 10 10 20 y (cotinine) 179 283 75.6 174 209 9.51 350 1.85 43.4 25.1 408 344

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Consider the paired data: I 1.42 4.22 9.16 4.11 12.28 28.62 7.92 24.82 9.59 29.82 Find estimates for the linear model y, = Bo+81₁+e, where ,~ N(0, ²). That is find 3o. 3₁, 6. Also perform a test of the null hypothesis Ho 3₁0 at level a=0.01.