sorry, didnt have the time at that particular moment.
well i had to randomly select data off a sheet, the data showed different regions, and then displayed that regions Co2 emissions and the regions GNI (gross national income). After randomly selecting a region, i was asked to select a starting year between 1970 and 2000 and then a continuous period of 12 years.
The data i randomly selected is as follows:
Sub-Saharan Africa year Co2 emissions GNI
1972: 0.88 230
1973: 0.91 270
1974: 0.94 360
1975: 0.89 410
1976: 0.91 430
1977: 0.88 450
1978: 0.86 470
1979: 0.94 560
1980: 0.93 660
1981: 0.96 700
1982: 0.94 650
1983: 0.94 560
Most of the questions relate to comparing or displaying my regions data against the data for the world.
the worlds data is as follows:
year Co2 emissions GNI
1972: 4.00 960
1973: 4.12 1160
1974: 4.03 1360
1975: 3.97 1520
1976: 4.13 1590
1977: 4.16 1690
1978: 4.25 1900
1979: 4.29 2240
1980: 4.20 2570
1981: 4.03 2660
1982: 3.94 2520
1983: 3.91 2390
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Question 1. construct a scatterplot to investigate the nature of the relationship between Co2 emissions (as the independant variable) and the GNI for your selected region.
Question 2. assuming the relationship is linear, use the scatterplot data to perform a full regression analysis. ie. calculate the equation of the least squares regression line, calculate the correlation coefficient and the coefficient of determination, and graph a residual plot. (provide a sketch of the residual plot).
Question 3. Use the equation to interpolate and extrapolate (one value of each) within the range of the original data supplied. Comment on the reliability of each of these predictions.
Question 4. Write a report on the results of the regression analysis.
Question 5. Based on your regression analysis, discuss the suitability of using a linear model to represent the data. If the data was non-linear, suggest appropriate transformations that may linearise the relationship between the co2 emissions and GNI. Explain how these transformations would linearise the data.
Question 6. construct a time series plot of co2 emissions for your selected region and time for the world on one set of axes.
Question 7. comment on any trends in the two time series plots.
Question 8. Assuming the data is linear, find the equation of the least squares regression trend line for each set of data. Use the trend lines to forecast the co2 emissions for your selected region and for the world in 2010.
PLEASE HELP
