Economic Data Collection and Analysis Essay Example for Free

Economic Data Collection and Analysis Essay From analysing the Data on the Scatter Plot the relationship between the GDP and the Population of Great Britain from 1999-2009 appears to be a moderate positive correlation relationship. Both variables are increasing at a similar rate and following a similar pattern which would indicate this relationship. This relationship would tend to be a positive one as more people are available to the work. Question 3 The correlation relationship between the GDP and the Population represents a strong positive correlation at 0.897922049. This indicates that the two indicators have a close relationship and any change in either of the indicators will be represented by a similar change in the other. This figure is close to 1 which would indicate a perfectly positive correlation relationship. This would indicate that Population was a perfect indicator for Great Britain’s GDP. Question 4 The correlation of determination indicates a variation of 80.6%. This means that 80.6% of variation in Great Britain’s GDP can be accounted to the nation’s Population variation. This is a large percentage and represents the strong relationship between Great Britain’s population and GDP. This figure indicates a proportion of the total variation in the dependent variable, population that is explained by the variation in the independent variable GDP. This figure is easier interpreted compared to the correlation relationship due to its percentage format. Question 5 The Slope of these two indicators is 77.038. This figure means that for every addition to Great Britain’s population, GDP will increase by  £77.03. This Figure represents further the close relationship between Great Britain’s population and GDP. The intercept coefficient of these indicators is -3375.39. This figure indicates that if Great Britain’s population dropped to zero that the nation’s GDP would also fall to this figure. Question 6 Using the Ordinary Least Squares technique I plotted the regression line for this scatter diagram. Using this method the regression line is best fit to this scatter diagram. This regression is in accordance with the data represented in Question 3 and Question 4 shown above. This regression line expresses the relationship between the two variables and estimates the value of the dependent variable, GDP based on a selected value of the independent variable population. Based on the population of Great Britain the standard error of the GDP in the Nation is 41.55%. This indicates how precise the estimation of GDP is depending on the population of Great Britain. Part 2: Question 2: The Data from the scatter plot would indicate the relationship between the Unemployment and Gross National Saving in the United States from 1999-2009 was a negative correlation relationship. This relationship would be negative due to the loss of income expeirenced as workers become unemployed. Question 4: The correlation coefficient represents a strong relationship between unemployment and GNS in the United States from 1999-2009 at -0.857874442. This correlation indicates that both of these indicators are closely linked and influential towards each other. This relationship is a strong negative correlation as forecasted above. Question 5: The correlation of determination stands at 73.5%. This indicates a close relationship between the unemployment and GNS in the United States from 1999-2009. This figure means that 73.5% of the variation in Gross National Saving can be accounted for by the variation in unemployment in the United States during the same period. The percentage format of this figure makes it easier to comprehend. Question 6: The slope of this correlation stands at -1.32 which would imply that the law of diminishing marginal returns is applying. This means that for every additional person in unemployment the GNS will fall. The intercept coefficient of these indicators is 22.143. This figure indicates that if unemployment were to fall to zero that Gross National Savings would change to this figure.