The regression specified for private investment is I = a1 + a2 Y + a3 CRD + u . The results fromestimating the regression are presented below. The sample covers the annual series spanningfrom 1981-2020 (n=40).III-Î, = 2.4 + 0.75 Y, + 0.45 CRD,(1.02) (0.26) KO.12)R? = 0.78D-W-d= 1.95where I, Y and represent real private investment, real GDP and real credits respectively.Suppose you would like to perform the test for the first order autocorrelation using the LM type testtechnique. Define the auxiliary regression. Also suppose you found R-squared from the auxiliary regressionto be 0.082, perform the LM test for the first order autocorrelation and interpret the result.

The given data is as follows:The regression model is Sample size,

Answered: III- The regression specified for…

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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A regression was run to determine if there is a relationship between hours of study per week (x) and the final exam scores (y).The results of the regression were: y=ax+b a=5.088 b=26.56 r2=0.913936 r=0.956 Use this to predict the final exam score of a student who studies 4.5 hours per week, and please round your answer to a whole number.
A regression was run to determine if there is a relationship between hours of study per week (x) and the final exam scores (y). The results of the regression were: y=ax+b a=6.239 b=38.43 r²=0.758641 r=0.871 Use this to predict the final exam score of a student who studies 6 hours per week, and please round your answer to a whole number.
Data was recorded for the temperature, in degrees Celsius, of a cup of coffee over a 30-minute period. Given the regression equation, In(Temp) = 4.20 0.023(Time), what is the predicted temperature after 3 minutes? 33.45 °C 62.24 °C 65.17 °C 66.69 °C
Heights (cm) and weights (kg) are measured for 100 randomly selected adult males, and range from heights of 134 to 192 cm and weights of 40 to 150 kg. Let the predictor variable x be the first variable given. The 100 paired measurements yield x = 166.94 cm, y = 81.26 kg, r= 0.352, P-value = 0.000, and y = - 101 + 1.04x. Find %3D the best predicted value of y (weight) given an adult male who is 145 cm tall. Use a 0.10 significance level. The best predicted value of y for an adult male who is 145 cm tall is kg. (Round to two decimal places as needed.)
A regression was run to determine if there is a relationship between hours of study per week (x) and the final exam scores (y). The results of the regression were: y=ax+b a=5.865 b=25.06 r²=0.81 r=0.9 Use this to predict the final exam score of a student who studies 4.5 hours per week, and please round your answer to a whole number.
A regression was run to determine if there is a relationship between hours of study per week (x) and the final exam Scores (y). The results of the regression were: y=ax+b a=6.179 b=28.96 r²=0.937024 r=0.968 Use this to predict the final exam score of a student who studies 4 hours per week, and please round your answer to a whole number.
The linear regression equation for predicting systolic blood pressure from age is: y = 54 + 1.6*x Find the residual for a person who is 32 years of age with a systolic blood pressure of 103.9 (round your answer to one decimal place)
A regression was run to determine if there is a relationship between hours of TV watched per day (xx) and number of situps a person can do (yy).The results of the regression were:y=ax+b a=-0.629 b=39.045 r2=0.806404 r=-0.898 Use this to predict the number of situps a person who watches 6.5 hour(s) of TV can do, and please round your answer to a whole number.
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=ax+b a=-1.075 b=27.958 r2=0.919681 r=-0.959 Use this to predict the number of situps a person who watches 12 hours of TV can do (to one decimal place)

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