1305AFE Business Data Anlysis

According to the Housing Mobility section of the General Social Survey, Victoria, 2006 (ABS, Catalogue Number: 4159.2.55.001), about 1494 thousand people aged 18 years or over moved in the last five years. Of these people, 758.4 thousand moved for housing reasons, 170.2 thousand moved for employment reasons, 398.6 thousand moved for family reasons and 167.2 thousand moved for other reasons.
a. Construct a pie chart
b. Interpret your pie chart.
Assume you are a Data Analyst in an international economic consultancy firm. Your team leader has given you a research task to investigate the empirical relationship between China’s export volumes and per capita GDP (Gross Domestic Product).
Relevant Variables: China’s Export volume index and China’s GDP per capita (constant 2010 US$). (Annual time series data (for the period 1980 – 2018) from the World Bank - World
development indicators database)The data are stored in the file named “ASSIGNMENTDATA.XLSX” in the course website. Using EXCEL, answer below questions:
1. Using an appropriate graphical descriptive measure (relevant for time series data) describe the two variables
2. Use an appropriate plot to investigate the relationship between Export volume index and GDP per capita. Assume Export volume index as an independent variable. Interpret the plot.
3. Prepare a numerical summary report about the data on the two variables by including the summary measures, mean, median, range, variance, standard deviation, coefficient of variation, smallest and
largest values, and the three quartiles, for each variable.
4. Calculate the coefficient of correlation (r) between Export volume index and GDP per capita. Then, interpret it.
5. Estimate a simple linear regression model and present the estimated linear equation. Then, interpret the coefficient estimates of the linear model.
6. Determine the coefficient of determination R2 and interpret it.
7. Test whether GDP per capita positively and significantly increases with export volume index at the 5% significance level.
8. What is the value of the standard error of the estimate (se). Then, comment on the fitness of the linear regression model?