Goto www.gapminder.org. Click on “Wealth & Health of Nations” under the “Explore the world” title. Wait until it finishes initializing. It displays the Life Expectancy in Years, and GDP in Dollars for a wide number of nations, for 2007. On the next screen click the “Full screen” button.
On the 2007 sheet select The Netherlands, India, China, and Niger in the country list on the right hand side. Read their GDP and Life Expectancy data from the website and put it into an Excel spreadsheet. Do the same for South Africa, Botswana, and Vietnam.
a) Use Excel to determine the correlation between GDP and Life Expectancy for the first sample, made up of The Netherlands, India, China and Niger. Calculate the correlation coefficient and explain what it tells you.
b) Calculate the R-square for the first sample (The Netherlands, India, China, Niger). Explain what the R-square is and what the R-square results tell you in this example.
c) Draw a research model with GDP as Independent Variable and Life Expectancy as Dependent Variable.
e) State H0 and HA for the hypothesized relationship between GDP and Life Expectancy.
f) Use Excel to run a linear regression analysis between GDP and Life Expectancy. Use the LINEST function in Excel, as well as Excel’s Help function to do that. It returns the Intercept and the Slope. What is the regression formula for the first sample (comprising The Netherlands, India, China, and Niger)? What does it tell you?
g) Calculate the increase in Life expectancy (in hours) with every $ increase in GDP.
h) Repeat the calculations done in a), b), f) and g) for the wider sample, including The Netherlands, India, China, Niger, South Africa, Botswana, and Vietnam. What are the differences in R-square and increase in Life Expectancy with every Dollar increase in GDP? Would the understanding of the data and results change if you look at both samples independently? Reflect on the results.
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