Concept explainers
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Explanation of Solution
The formulas for sum of squares are as follows:
The total sum of squares is calculated is as follows:
Consider
Thus, the required TSS is as follows:
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Chapter 13 Solutions
Mathematical Statistics with Applications
- Find the least-squares regression line ŷ = bo + bjx through the points (-2, 0), (3, 7), (5, 14), (9, 19), (12, 26), and then use it to find point estimates ŷ corresponding to x = 4 and x = 10. For x = 4, y = For x = 10, y =arrow_forwardN(0, o?) is For the simple linear model Y = a + BX + €, where the error variable e ~ independent of X, use the law of total variance to show that Var(Y) = 3² Var(X)+o².arrow_forwardFind the least-squares regression line ŷ = bo + b1r through the points %3D (-1,2), (2, 6), (5, 13), (7, 20), (10, 23), and then use it to find point estimates y corresponding to x = 3 and x = 6. For = 3, y = %3D For I = 6, y = %3Darrow_forward
- Use a table to obtain the formula for the best least-squares fit to the data following data points: (1,2) (2, 3) (3,7) (4,9) (5, 12) Results from your Table ● Σα ● X = Συ · Σxy Σα2 Regression Line •y= - -arrow_forwardUse the general equation for the least square regression line to show that this line always passes through the point (x,y) * bars above the x and y.That is, set x=x(with a bar above the x) and show that the line predicts that y=y (with a bar above the y).arrow_forwardDo fast i will give like soonarrow_forward
- Find the least-squares regression line ŷ =b0+b1x through the points (-2,2), (2,6), (5,13),(8,20),(10,24). For what value of x is ŷ =0? x =?arrow_forwardConsider the linear model y=B,+B,x,+B,x,,+B,x+B,+u, You estimate the model y =B,+B,x,+B,x, observations and obtain the OLS residuals . You then estimate the auxiliary regression +u based on 123 31 3" 3i 41 The LM statistic +1 4/ you obtain to test the null hypothesis that H:B,=B,=0 is 20.91. What is the R2 of the auxiliary regression? It is not possible to say O 0.17 O 0.175714 0.177203arrow_forwardFind the least-squares line y = Po + Bx that best fits the given data. O A. y=0.7-0.03x O B. y= 3.8+0.04x OC. y 0.04 +3.8x (-3,2), (-2,5). (0,5). (2,2). (3,2) Suppose the errors in measuring the y-values of the last two data points are greater than for the other points. Weight these data points half as much as the rest of the data O D. y= 4.2-0.03x 1-3 2 1 - 2 B1 X= 1 1. 2 3. 2. 552N 2arrow_forward
- Consider a simple linear regression model, Y₁ = Bo + B₁X₁ + ₁ for i=1,2,...,n with the usual random error term (&) assumptions. Suppose that hypotheses Ho: P₁ = 0 against H₁:₁ <0 were tested and Ho: B₁ = 0 was rejected. Assume ₁e₁² = 0. ei i) Briefly explain what the conclusion of the test means for the values of Y given the values of X. -1 ii) Draw an example of a scatter plot with the fitted regression line for the problem mentioned above. iii) Calculate and interpret the correlation coefficient for the problem at hand.arrow_forwardConsider the following regression model Yt = β0 + β1 Ut + β2 Vt + β3 Wt + β4Xt + ∈t , where U, V, W, X and Y are economic variables observed from t = 1, . . . , 75, β0 , . . . , β4 are the model parameters and ∈t is the random disturbance term satisfying the classical assumptions. Ordinary Least Squares (OLS) is used to estimate the parameters, producing the following estimated model: Yt = 1.115 + 0.790*Ut − 0.327*Vt + 0.763*Wt + 0.456*Xt (0.405) (0.178) (0.088) (0.274) (0.017) where standard errors are given in parentheses, the R-squared = 0.941, the Durbin-Watson statistic is DW = 1.907 and the residual sum of squares is RSS = 0.0757. In answering this question, use the 5% level of significance for any hypothesis tests that you are asked to perform, state clearly the null and al- ternative hypotheses that you are testing, the test statistics that you are using and interpret the decisions that you make.…arrow_forwardThe number of murders and robberies per 100,000 population for a random selection of states are shown. Find the equation of the regression line y'=ax+b, and predict the number of robberies when x=4.5 murders murders,x: 2.4,2.7,5.6,2.6,2.1,3.3,6.6,5.7 robberies,y : 25.3,14.3,151.6,91.1,80,49,17.3,45.8arrow_forward
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