QUESTION 2In the macro relation between GDP and FDI, Dr Mudenda obtained the following valuesfrom a Stata output: FDI coefficient of 0.45; t-statistic of 3; and covariance (GDP, FDI)value of 0.41. In literature, this relationship between GDP and FDI has generally beenestablished to be statistically significant. Answer the following questions:i) Calculate the variance of the FDI variable and explain its implicationii)Use the confidence interval approach to test whether FDI's influence on GDP isstatically significant or not in Dr Mudenda's study. Use 5% level which gives 1.96critical values.What is the expected value of the p-values for studies that have been conductedin literature?

In the given regression model, the relationship between GDP and FDI are studied. GDP is the…

Answered: In the macro relation between GDP and…

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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The Minitab output shown below was obtained by using paired data consisting of weights (in Ib) of 27 cars and their highway fuel consumption amounts (in mi/gal). Along with the paired sample data, Minitab was also given a car weight of 4500 lb to be used for predicting the highway fuel consumption amount. Use the information provided in the display to determine the value of the linear correlation coefficient. (Be careful to correctly identify the sign of the correlation coefficient.) Given that there are 27 pairs of data, is there sufficient evidence to support a claim of linear correlation between the weights of cars and their highway fuel consumption amounts? Click the icon to view the Minitab display. Minitab output The linear correlation coefficient is. (Round to three decimal places as needed.) The regression equation is Highway = 50.4- 0.00535 Weight %3D Predictor Сoef SE Coef T Constant 50.383 2.732 17.75 0.000 Weight - 0.0053502 0.0007856 -7.55 0.000 S= 2.17876 R-Sq = 65.1% R-…
The Minitab output shown below was obtained by using paired data consisting of weights (in lb) of 31 cars and their highway fuel consumption amounts (in mi/gal). Along with the paired sample data, Minitab was also given a car weight of 4000 lb to be used for predicting the highway fuel consumption amount. Use the information provided in the display to determine the value of the linear correlation coefficient. (Be careful to correctly identify the sign of the correlation coefficient.) Given that there are 31 pairs of data, is there sufficient evidence to support a claim of linear correlation between the weights of cars and their highway fuel consumption amounts? Click the icon to view the Minitab display. The linear correlation coefficient is (Round to three decimal places as needed.) Is there sufficient evidence to support a claim of linear correlation? Yes O No Minitab output The regression equation is Highway = 50.8 -0.00508 Weight Predictor Coef SE Coef T P Constant 50.772 2.793…
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