which of the following statement is true concerning the Cobb-Douglas regression for Tunisia shown the figure belowA. The natural log of per-capita income is shown as a function of the natural log of the capital-to-labor ratio, and capital's share of income is 0.0369B The natural log of per-capita income is shown as a function of the natural log of the capítal-to-labor ratio, and labor's share of income is 0.3111C None of the choices given is correct.eD The natural log of per-capita income is shown as a function of the natural log of the capital-to-labor ratio, and labor's share of income is 0.0369E The natural log of per-capita income is shown as a function of the natural log of the capital-to-labor ratio, and capital's share of income is 0.3111i wanna solution ...how to do it ...not only for the answer The graph represents a linear regression analysis over the period from 1994 to 2017. It is a scatter plot with a fitted line showcasing the relationship between the natural logarithm of $ K/L $ (x-axis) and the natural logarithm of $ Y/L $ (y-axis).### Key Details:- **Title**: TUN: 1994 to 2017- **Equation of the Line**: $ y = 0.3111x + 0.0396 $ - This indicates a positive linear relationship, with a slope of 0.3111, suggesting that as $ \ln(K/L) $ increases, $ \ln(Y/L) $ increases as well.- **Coefficient of Determination ($ R^2 $)**: 0.9384 - This high $ R^2 $ value indicates that approximately 93.84% of the variation in $ \ln(Y/L) $ is explained by the model, suggesting a strong fit.- **Dots**: Represent individual data points from each year's observations between 1994 and 2017.- **Line**: Represents the best fit line derived from the linear regression model.The graph visually describes the strength and nature of the relationship between the variables over the specified period, highlighting a strong correlation as depicted by the closely clustered data points around the line of best fit.

The Cobb-Douglas regression can be shown as; y=bxαL1-αy=bxαLLαyL=bxLα On taking natural log both…

Answered: which of the following statement is…

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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which of the following statement is true concerning the Cobb-Douglas regression for Tunisia shown the figure below

A. The natural log of per-capita income is shown as a function of the natural log of the capital-to-labor ratio, and capital's share of income is 0.0369

B The natural log of per-capita income is shown as a function of the natural log of the capítal-to-labor ratio, and labor's share of income is 0.3111

C None of the choices given is correct.e

D The natural log of per-capita income is shown as a function of the natural log of the capital-to-labor ratio, and labor's share of income is 0.0369

E The natural log of per-capita income is shown as a function of the natural log of the capital-to-labor ratio, and capital's share of income is 0.3111

i wanna solution ...how to do it ...not only for the answer

The graph represents a linear regression analysis over the period from 1994 to 2017. It is a scatter plot with a fitted line showcasing the relationship between the natural logarithm of $ K/L $ (x-axis) and the natural logarithm of $ Y/L $ (y-axis).

### Key Details:
- **Title**: TUN: 1994 to 2017
- **Equation of the Line**: $ y = 0.3111x + 0.0396 $
- This indicates a positive linear relationship, with a slope of 0.3111, suggesting that as $ \ln(K/L) $ increases, $ \ln(Y/L) $ increases as well.
- **Coefficient of Determination ($ R^2 $)**: 0.9384
- This high $ R^2 $ value indicates that approximately 93.84% of the variation in $ \ln(Y/L) $ is explained by the model, suggesting a strong fit.
- **Dots**: Represent individual data points from each year's observations between 1994 and 2017.
- **Line**: Represents the best fit line derived from the linear regression model.

The graph visually describes the strength and nature of the relationship between the variables over the specified period, highlighting a strong correlation as depicted by the closely clustered data points around the line of best fit.

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