s) Use the Durbin-Watson test to test, at 5% level of significance, for thepresence of significant linear correlation among error terms in the followingcases:a) Given that the sample size is n=20, the Durbin Watson (DW) statistic 0.62, whenthe regression model is of the form E(Y) = Bo + B,Xb) Given that the sample size is #=35, the Durbin Watson (DW) statistic = 1.82, whenthe regression model is of the form E(Y) = Bo + B,X, + B,X2.c) Given that the sample size is n-40, the Durbin Watson (DW) statistic =2.78, whenthe regression model is of the form E(Y) = Bo + BzX, + B2X2 + B,X3 +B,X4Table Criical value for the Durbin-Watson d Statistic (a = 05)

Null Hypothesis: H0: There is no significant linear correlation among the error terms. Alternative…

Use the Durbin-Watson test to test, at 5% level of significance, for the presence of significant linear correlation among error terms in the following cases: Given that the sample size is n=20, the Durbin Watson (DW) statistic = 0.62, when the regression model is of the form E(Y) = Bo + B1X %3D Given that the sample size is n=35, the Durbin Watson (DW) statistic 1.82, when the regression model is of the form E(Y) = Bo + B,X, + B2X2 %3D Given that the sample size is n=40, the Durbin Watson (DW) statistic 2.78, when the regression model is of the form E(Y) = Bo + B,X1 + B2X2 + B3X3+ B4X4 %3D

Use the Durbin-Watson test to test, at 5% level of significance, for the presence of significant linear correlation among error terms in the following cases: Given that the sample size is n=20, the Durbin Watson (DW) statistic = 0.62, when the regression model is of the form E(Y) = Bo + B1X %3D Given that the sample size is n=35, the Durbin Watson (DW) statistic 1.82, when the regression model is of the form E(Y) = Bo + B,X, + B2X2 %3D Given that the sample size is n=40, the Durbin Watson (DW) statistic 2.78, when the regression model is of the form E(Y) = Bo + B,X1 + B2X2 + B3X3+ B4X4 %3D

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

A local real estate agent argues that house prices in Pittsburgh are related tothe number of rooms in a house. You collect a random sample of 190 houses and run asimple regression using House Price (measured in dollars) as the dependent variableand Rooms (measured as the number of rooms in a house) as the independentvariable. Given below is the Excel output of the regression results. (a) Construct the 99.7% confidence interval for the slope of the regressionline.(b) Consider a house with 5 room. What is the probability that the housewill sell for more than $270,245?(c) A savvy real estate investor, Noah, owns a house in Pittsburgh thathe is planning to sell. Based on the regression put, Noah decides to destroy somewalls to reduce the number of rooms in the house, hoping to increase the houseselling price. Based on the regression output, do you think this is a good decision?Justify your comment.
A multiple regression was estimated using the SEK method and the results are given below. Based on these estimates alone, multiple Explain the level of linearity, varying variance and cascading dependency problems. Bi: 4,1234 B2: -0,2189 B3: -1,7862 sh:3,1223 R?: 0,9820 R*: 0,9750 F: 10,89 F tablo:3,07 sh:4,4420 sh:0,3179 D.W.: 0,2558 d1:0,385 dy:1,685
A student used multiple regression analysis to study how family spending (y) is influenced by income (x1), family size (x2), and additions to savings (x3). The variables y, x1, and x3 are measured in thousands of dollars. The following results were obtained. ANOVA df SS Regression 3 45.9634 Residual 11 2.6218 Total Coefficients Standard Error intercept 0.0136 x1 0.7992 0.074 x2 0.2280 0.190 x3 -0.5796 0.920 answer please : 1: Carry out a test to see if x3 and y are significantly related. Use a 5% level of significance.
41
A student used multiple regression analysis to study how family spending (y) is influenced by income (x) family size (x2), and addition to savings(x3). The variables y, x1, and x3. The variables y, x1, and x3 are measured in thousands of dollars . The following results were obtained. ANOVA df SS Regression 3 45.9634 Residual 11 2.6218 Total Coefficient Standard Error Intercept 0.0136 X1 0.7992 0.074 X2 0.2280 0.190 X3 -0.5796 0.920 Write out the estimated regression equation for the relationship between the variables. Compute coefficient of determination. What can you say about the strength of this relationship? Carry out a test to determine whether y is significantly related to the independent variables. Use a 5% level of significant. Carry out a test to see if X3 and y are significantly related. Use a 5% level of significance
The table below lists measured amounts of redshift and the distances (billions of light-years) to randomly selected astronomical objects. There is sufficient evidence to support a claim of a linear correlation, so it is reasonable to use the regression equation when making predictions. For the prediction interval, use a 90% confidence level with a redshift of 0.0126. Find the explained variation. Redshift Distance OA, 0.157904 OB. 0.444904 OC. 0.000582 OD. 0.219582 0.0231 0.34 0.0536 0.76 0.0715 0.99 0.0391 0.56 0.0438 0.63 0.0109 0.15
Shown below is a portion of a computer output for regression analysis relating y (dependent variable) and x (independent variable). ANOVA df SS Regression 1 24.061 Residual 10 67.979 Coefficients Standard Error Intercept 11.064 2.049 x −0.566 0.301 (a) What has been the sample size for the above regression analysis? (b) Perform a t-test and determine whether or not x and y are related. Let ? = 0.05. State the null and alternative hypotheses. (Enter != for ≠ as needed.) H0: Ha: Find the value of the test statistic. (Round your answer to three decimal places.) Find the p-value. (Round your answer to four decimal places.) p-value = What is your conclusion? .
The following sample contains the scores of 6 students selected at random in Mathematics and English. Use the scores in English as the dependent variable Y. Mathematics score (X) 70 92 80 74 65 83 English score (Y) 74 84 63 87 78 90 ∑x=464, ∑y=476,∑x^2=36354,∑y^2=38254, ∑xy=36926. Estimate the regression parameters and also write the prediction equation.
A student used multiple regression analysis to study how family spending (y) is influenced by income (x1), family size (x2), and additions to savings(x3). The variables y, x1, and x3 are measured in thousands of dollars. The following results were obtained. ANOVA df SS Regression 3 45.9634 Residual 11 2.6218 Total Coefficients Standard Error Intercept 0.0136 x1 0.7992 0.074 x2 0.2280 0.190 x3 -0.5796 0.920 Write out the estimated regression equation for the relationship between the variables. Compute coefficient of determination. What can you say about the strength of this relationship? Carry out a test to determine whether y is…
i)Test individually whether the slope coefficients are significant at 10% significance level. ii)Test the overall significance of the estimated regression at 1% significance level.
The value obtained for the test statistic, z, in a one-mean z-test is given. Also given is whether the test is two tailed, left tailed, or right tailed. Also is given the P-value.A left-tailed test: z = -1.17 P-value: 0.1210 Use technology to create a scatter plot of the data from the previous question. Include the regression line. (Hand drawn graphs will not be accepted.) The explanatory (input) variable and the response (output) variable must be clearly labeled, within the context of this problem.
Police sometimes use footprint evidence to estimate the height of a suspect. Data was collected from 36 randomly selected men in Nebraska in 2001. The regression model assumptions have been checked, and they are all satisfied. We want to test if there is a positive linear association between shoe print size and average height. The p-value of the appropriate test was found to be 0.0006. (a) Give your brief conclusion. Note that no significance level is provided. (b) Give your conclusion in the context of the problem. (This question will be marked manually by your instructor).