Quantitive analyse Essay Example | Topics and Well Written Essays - 1000 words

Quantitive analyse - Essay Example There appears very strong linear relationship between income and age, as the data points lie (cluster) around a straight line. There appears very week (or no) linear relationship between income and degree. However, the scattergraph is inconclusive, as there are two values for degree Arts (0) and Science (1), only. In a bivariate regression, R2 is a measure of the correlation coefficient r. Correlation coefficient value near 0 indicates there is little (or no) association between the two variables and a value near 1 indicates a strong association between the two variables (Lind, Marchal and Wathen, 2009). Using correlation coefficient, R2 can be calculated as below The regression slope coefficient of 0.771 suggests that every year increase in fulltime-employed adult’s age increases income by about  £771, on average. The regression intercept coefficient of 4.860 is not meaningful in the context of this problem because there will be no employee with 0 years age. The value of coefficient of determination, R2 is 0.9797. This suggests that fulltime-employed adult’s age explains about 97.97% variation in income. Only 2.03% variations in income remains unexplained. The regression slope coefficient of -2.35 and intercept coefficient of 37.71 suggests that Science degree decreases fulltime-employed adult’s income by about  £2,350 as compared to Arts degree. Arts fulltime employed adult’s income is  £37,710, on average. The value of coefficient of determination, R2 is 0.0183. This suggests that fulltime-employed adult’s degree only explains about 1.83% variation in income and 98.17% variations in income remains