Question 16The standard error of the regression is essentially a measure of:A. The standard deviation of the intercept coefficientB. The standard deviation of the slope coefficientC. The standard deviation of the dependent variableD. The standard deviation of the residualE. None of the aboveAOBOCE If the sample covariance is positive then:A. The sample correlation coefficient is necessarily positiveB. The sample correlation coefficient is most likely positive but could be negativeC. The sample correlation is equally likely to be positive or negativeD. The sample correlation coefficient is most likely negative but could be positiveE. The sample correlation coefficient is necessarily negativeА« PreviousNeB.

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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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Use the value of the linear correlation coefficient to calculate the coefficient of determination. What does this tell you about the explained variation of the data about the regression line? About the unexplained variation? r = 0.444 Calculate the coefficient of determination. (Round to three decimal places as needed.)
For variables X and Y we have that the correlation between them is 0.9. Also the standard deviation of Y is 8, while the standard deviation of X is 2. What is the slope of the regression equation that attempts to predict Y from X? Use two decimal places in your answer. Your Answer:
A simple regression model for 10 pair of data resulted in a standard error of 3.95 (i.e., Se = 3.95), and the. The sum of squares of error (SSE) is ______. a. 187.23 b. 171.63 c. 156.03 d. 140.42 e. 124.82
A residual plot from a simple linear regression analysis is shown to the right. Use the plot to answer the question below. residuals 0 X Which of the following statements regarding the plot is true? OA. The condition that the residuals are normally distributed is not met since not all of the residuals fall on the reference line in the residual plot. OB. The condition that the residuals have constant variation is met since the lines connecting the largest positive residuals and largest negative residuals are parallel. Oc. The condition that the residuals are normally distributed is not met since there is a diamond shape to the residuals in the residual plot. OD. The condition that the residuals have constant variation is not met since the variation increases and then decreases as x gets larger.
An econometric model is a multiple linear regression model if Question 10Select one: a. it explains the average value of y as a linear function of several explanatory variables b. it explains the sample mean of y as a function, linear in the parameters , of several x c. it explains y as a linear function of several x , the explanatory variables d. it explains the average of y as a function of several x e. none of the answers is correct
An automobile rental company wants to predict the yearly maintenance expense (Y) for an automobile using the number of miles driven during the year () and the age of the car (, in years) at the beginning of the year. The company has gathered the data on 10 automobiles and run a regression analysis with the results shown below:. Summary measures Multiple R 0.9689 R-Square 0.9387 Adj R-Square 0.9212 StErr of Estimate 72.218 Regression coefficients Coefficient Std Err t-value p-value Constant 33.796 48.181 0.7014 0.5057 Miles Driven 0.0549 0.0191 2.8666 0.0241 Age of car 21.467 20.573 1.0434 0.3314 Use the information above to estimate the annual maintenance expense for a 10 years old car with 60,000 miles.
3. Regression analysis breaks scores on the DV into... (explain and give equations)

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The standard error of the regression is essentially a measure of: A. The standard deviation of the intercept coefficient B. The standard deviation of the slope coefficient C. The standard deviation of the dependent variable D. The standard deviation of the residual E. None of the above