The quarterly data obtained from the table were exported to excel to help in carrying the test analysis. Further, the inflation rates were identified for the two countries by making use of the customer price indices (av)-LCPI instead of the LCU used for the exchange rate.The regression equation is “change In The Exchange Rates = - 0.0109 + 0.0025 US inflation”. An especially high P value of 0.857 = 85.7% results from the probability coefficient of 0. There are only -0.17 standard errors, an indicator that the model is less than 95% confidence interval. As indicated the standard deviation is "0.0463921 and the "R-Sq" 14%. From this the "R-Sq (adj)" = 0.4% implies that the model does not fit at all in the ‘Change In The Exchange Rates versus US Inflation’ as shown in the following scatterplot.The regression equation is “change In The Exchange Rates = - 0.0113 + 0.0027 UK inflation”. A high value of 0.849 = 84.9% is realized for the probability of coefficient of 0. There are only -0.23 standard errors, which mean that it is less than 95% confidence interval. The value for "S" 0.0463729 provides the estimate for the standard deviation, and the "R-Sq" 0.14 (14%) is the indicator of how the model fits the data. This result to an "R-Sq (adj)" of 0.0% consequently the model does not fit the data.The statistical model was crucial in constructing a straight-line predictor in which case the change In The Exchange Rates = - 0.0113 + 0.0027 UK inflation represents the regression line about which all values for change In The Exchange Rates and UK inflation fall. As can be noted from the scatterplot chart UK inflation is stable since percentage change fluctuates from -0.5 to 2.0 and the trend increases.The regression equation is change In The Exchange Rates = - 0.0124 + 0. The probability that the coefficient is 0.00270 points to a relatively higher value of 0. There are only 0.26 standard errors, which mean that it is more than 95% confidence interval. The standard deviation "S" 0.0463633 shows the actual deviation from the mean, and the "R-Sq" 0.6 (60%) depicts how the model fits the data therein.
Please type your essay title, choose your document type, enter your email and we send you essay samples