Interpret the following. Dependent Variable: URMethod: Least SquaresDate: 10/31/22 Time: 09:47Sample: 1991 2021Included observations: 31VariableсINFR-squaredAdjusted R-squaredS.E. of regressionSum squared residLog likelihoodF-statisticProb(F-statistic)CoefficientStd. Error t-Statistic-100.448022.043749.969152 1.629152 6.119226-4.556760 0.00010.0000Prob.0.563548 Mean dependent var0.548498S.D. dependent var28.54592Akaike info criterion23631.21 Schwarz criterion-146.8503Hannan-Quinn criter.37.44493 Durbin-Watson stat0.00000130.7434542.482929.6032469.6957619.6334031.023352

From the variable table, we get to know that if INF is independent variable and UR is dependent…

Answered: Dependent Variable: UR Method: Least…

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

The data points in ExerciseIn each of Exercises, we have presented two linear equations and a set of data points. For each exercise,a. plot the data points and the first linear equation on one graph and the data points and the second linear equation on another.b. construct tables for x, y,ŷ e, and e2 like Table (page 626).c. determine which line fits the set of data points better, according to the least-squares criterion.TABLEDetermining how well the data points in Table are fit by (a) Line A and (b) Line Ba. Line A: y= -1 + 2x x y ŷ e e2 1 3 1 2 4 2 1 3 -2 4 3 5 5 0 0 8 b. Line B: y= -1 + x x y ŷ e e2 1 3 2 1 1 2 1 3 -2 4 3 5 4 1 1 6 TABLE Three data points x y 1 3 2 1 3 5 Line A: y=3-0.6x, Line B: y=4-xData Points x 0 2 2 5 6 y 4 2 0 -2 1 ŷ =1+2x x 1 2 3 y 4 3 8
The data points in ExerciseIn each of Exercises, we have presented two linear equations and a set of data points. For each exercise,a. plot the data points and the first linear equation on one graph and the data points and the second linear equation on another.b. construct tables for x, y, e, and e2 like Table (page 626).c. determine which line fits the set of data points better, according to the least-squares criterion.TABLEDetermining how well the data points in Table are fit by (a) Line A and (b) Line Ba. Line A: y= -1 + 2x x y ŷ e e2 1 3 1 2 4 2 1 3 -2 4 3 5 5 0 0 8 b. Line B: y= -1 + x x y ŷ e e2 1 3 2 1 1 2 1 3 -2 4 3 5 4 1 1 6 TABLE Three data points x y 1 3 2 1 3 5 Line A: y=9 -2x, Line B: y=6-xData Points x 1 3 4 4 y 8 0 3 1
Concentric circles of radii 1 cm and 3 cm are drawn on a circular target radius 5 cm. A darts player receives 10, 5 or 3 points for hitting the target inside the smaller circle, middle annular region and outer annular region respectively. The player has only a 50-50 chance of hitting the target at all but if he does hit it he is just as likely to hit any one point on it as any other. If X = ‘number of points scored on a single throw of a dart’ calculate the expected value of X.
Heteroskedasticity arises because of non-constant variance of the error terms. We said proportional heteroskedasticity exists when the error variance takes the following structure: Var(et)=σt^2=σ^2 xt. But as we know, that is only one of many forms of heteroskedasticity. To get rid of that specific form of heteroskedasticity using Generalized Least Squares, we employed a specific correction – we divided by the square root of our independent variable x. And the reason why that specific correction worked, and yielded a variance of our GLS estimates that was sigma-squared, was because of the following math: (Picture 1) Where var(et)=σ^2 according to our LS assumptions. In other words, dividing everything by the square root of x made this correction work to give us sigma squared at the end of the expression. But if we have a different form of heteroskedasticity (i.e. a difference variance structure), we have to do a different correction to get rid of it. (a) what correction would you use…
The least-squares regression equation is y=728.0x+14,705 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.8165. For every dollar increase in median income, the percent of adults having at least a bachelor's degree is ___%, on average. For a median income of $0, the percent of adults with a bachelor's degree is ____%.
Find the least squares regression line and calculate S, the sum of the squared errors. Use the regression capabilities of a graphing utility to verify your results.
The percentage of variation in the values of y explained by the least squares regression line is the correlation coefficient. the slope of the regression line. the coefficient of determination. ρ. the y-intercept of the regression line.
Explain Least Squares Regression Unbiased Estimators y^ Lemma
The least-squares regression equation is y=784.6x+12,431 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7962. In a particular region, 26.5 percent of adults 25 years and older have at least a bachelor's degree. The median income in this region is $29,889. Is this income higher or lower than what you would expect? Why?
The least-squares regression equation is y=620.6x+16,624 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7004. Interpret the slope.
The least-squares regression equation is y=620.6x+16,624 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7004. Predict the median income of a region in which 30% of adults 25 years and older have at least a bachelor's degree.
Find the least squares regression line for the data points. Graph the points and the line on the same set of axes.(−2, 0), (−1, 2), (0, 3), (1, 5), (2, 6)

SEE MORE QUESTIONS

Recommended textbooks for you

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

MATLAB: An Introduction with Applications

Statistics

ISBN:

9781119256830

Author:

Amos Gilat

Publisher:

John Wiley & Sons Inc

Probability and Statistics for Engineering and th…

Statistics

ISBN:

9781305251809

Author:

Jay L. Devore

Publisher:

Cengage Learning

Statistics for The Behavioral Sciences (MindTap C…

Statistics

ISBN:

9781305504912

Author:

Frederick J Gravetter, Larry B. Wallnau

Publisher:

Cengage Learning

Elementary Statistics: Picturing the World (7th E…

Statistics

ISBN:

9780134683416

Author:

Ron Larson, Betsy Farber

Publisher:

PEARSON

The Basic Practice of Statistics

Statistics

ISBN:

9781319042578

Author:

David S. Moore, William I. Notz, Michael A. Fligner

Publisher:

W. H. Freeman

Introduction to the Practice of Statistics

Statistics

ISBN:

9781319013387

Author:

David S. Moore, George P. McCabe, Bruce A. Craig

Publisher:

W. H. Freeman

SEE MORE TEXTBOOKS