examining country level data across 63 countries


    Click here to get an A+ paper at a Discount

    examining country level data across 63 countries

    Files : 1

    Order Instructions:

    see the attachment

    Uploaded Files (1)
    #         Details     File Type     Uploaded by     Size     Customer View
    1.        Name: Finished_Order_111592_1.docx
    Date: September 20, 2014, 11:25 am     Finished_Order    Admin    Size: 10.72 KB

    2A
    Run the following simple linear regression function on GDP per Capita and life expectancy. Present your regression table along with the interpretation of the intercept and slope coefficients. Additionally, conduct a hypothesis test to see if having 5 extra year of life expectancy could increase GDP per capita by more than $20,000. Show all steps for the hypothesis test and use
    Adjusted R squared is a coefficient of determination, which tells us the variation in the dependent variable due to changes in the independent variable. From the findings in the above table, the value of adjusted R squared was 0.25, an indication that there was variation of 25.1% GDP per Capita due to life expectancy at 95% confidence interval. This shows that 25.1 % changes in GDP can be caused by changes in life expectancy. R is the correlation coefficient, which shows the relationship between the study variables. From the findings shown in the table above, there was a weak relationship between the variables, therefore, at 95%, the hypothesis is rejected as shown by sig. of 0.111, which is beyond 0.005.

    Need a Professional Writer to Work on this Paper and Give you Original Paper? CLICK HERE TO GET THIS PAPER WRITTEN



    R    203
    R Square    0.41
    Adjusted R    0.25
    Stardard Error    2251.71765
    Observation    62

    ANOVA    df    ss    ms    f    Sig

    Regression    1    1.12111E    1.33E+07    2.617    0.111
    Residual    61    3.09111E    5070232.4
    Total    62    3.2121E

    coefficient    Stardard Error    P value    Lower 95%    Upper 95%
    Intercept    -5968.296    4294.492    0.17    0.021    0.081
    LIFEEXP    91.344    56.47    0.111    0.412    567

    The constant is -5968.296 and the slope of 91.334, therefore, conduct a hypothesis test to see if having 5 extra year of life expectancy could increase GDP per capita by more than $20,000 and using the equation of the line,,, Y = -5968.296 + 91.334(5 years),,which is – 5511.626 and therefore by 5 extra years the GDP will have decreased by – 5511.626 and this in line with the rejection of the hypothesis.

    3B
    Based on the multiple regression results you had in Part 3a, test the joint significance of the variables INFLATION, ARTICLE and POP on GDP. Show your steps/calculation and use .
    R    0.988
    R Square    0.975
    Adjusted R    0.973
    Stardard Error    2251.71765
    Observation    372.80081

    ANOVA    df    ss    ms    f    Sig

    Regression    5    3.14332    1.33E+07    452.767    0
    Residual    57    7921342    5070232.4
    Total    62    3.22111

    coefficient    Stardard Error    P value    Lower 95%    Upper 95%
    Intercept    359.356    130.798    0.008    0.021    0.081
    MKTCAP    0.193    0.106    0.74    0.412    567
    ENERGY    0.001    0    0.026    0.212    231
    IMPORT    -5.496    2.404    0    0.001    0.233
    ARTICLE    0.52    0.009    0.001    0.234    0.344
    POP    -1.8118    0    0.662    0.234    0.331

    Adjusted R squared is a coefficient of determination, which tells us the variation in the dependent variable due to changes in the independent variable. From the findings in the above table, the value of adjusted R squared was 0.988, an indication that there was variation of 98.8% GDP per Capita due to test of the joint significance of the variables INFLATION, ARTICLE and POP on GDP. There is a joint significance of the variables INFLATION, ARTICLE and POP on GDP. The findings in the table above show that there was a strong positive  relationship between the  joint variables and, therefore, at 95%, the hypothesis is rejected as shown by sig of 0.000, which is less than the prescribed 0.05 of rejecting the null hypothesis at 95% confidence interval.

    Need a Professional Writer to Work on this Paper and Give you Original Paper? CLICK HERE TO GET THIS PAPER WRITTEN

    Click here to get an A+ paper at a Discount


    Order This Paper Now

                                                                                                                                      Order Now