The analysis of the effect on time series and
Data
This paper used randomization processes in publishing statistical abstract from the TSP_Sample_econometric_1 informational data under
The
From
Methodology
The researcher investigated if there is no significant effect on crude ratio and
RESULTS
This section presents the analysis of the data on the study to find out if there is no significant effect on time series and
The descriptive statistics was also used in this study for the presentation purposes. Tables 1 to 2 show the significant effect on time series and
From Graph 1 , the researcher found out that majority of the elasticity have no changes except on IVAN elasticity and US gas ratio.
It can be gleaned in Graph 2 that Gulf gas ratio has slightly affected by the hurricane, this can be seen in weeks 291 to 320. It shows that the Ivan data has remarkable change in terms of time series under weeks 233 to 262 and 291 to 320. This reveals that there is a slight effect on time series and Gulf gas, in term of the Hurricane Katrina and Ivan TSP_Sample_econometric_1 informational data under
This paper examined the analysis of variance for
The Analysis of Variance was used to determine if there is no significant effect on crude ratio and US gas ratio, Gulf gas ratio, Cap ratio, stocks ratio ,Hurricane Katrina and Ivan TSP_Sample_econometric_1informational data. The result of the “Analysis of Variance” (ANOVA) shows that the value of compute F is greater than the tabulated F under
The Regression results are as follows: the unbiased estimator of the variance of the error in the multiple regression model is equal to .001. There is small value of MSE so the estimator is a good fit of the regression. Standard error of estimate is equal to 0.03145. Multiple coefficient of determination is .420 and an adjusted multiple coefficient of determination is equal to .412 showed that the data produced a good predictions.
The unbiased estimator of the variance of the error in the multiple regression model is equal to 0.001. There is a small value of MSE so the estimator of elasticity is a good fit of the regression. Standard error of estimate is equal to 0.3169. Multiple coefficient of determination is 0.411 and adjusted multiple coefficient of determination is equal to .403 showed that the data produced a good predictions.
Summary of the two multiple regression, the two findings reveals that the variables present in this study were good predictors of the gasoline stock price. This implies that even though there is a hurricane in the said countries the value of elasticity will remain controlled.
conclusion:
In this paper, the researcher empirically examined the success of the comparison between US and Gulf Coast gasoline stock price and the researcher investigated if there is no significant effect on crude ratio and US gas , Gulf gas, Cap, stocks in term of the Hurricane Katrina and Ivan TSP_Sample_econometric_1 informational data under Jan 7, 2000 to Dec 29, 2006. The researcher also used Frequency distribution and analysis of variance (ANOVA). The computation of the analysis of variance of US and
This paper examined the two countries that probably affected by the hurricane Katrina and Ivan. The two countries that are under this study were US and
The researcher discovered that there if there is a significant effect on crude ratio and US gas ratio , Gulf gas ratio, Cap ratio, stocks ratio, Hurricane Katrina and Ivan TSP_Sample_econometric_1 informational data under
This means that other variables can affect the flaws of the gasoline stock price. The researcher suggested the additional parameters for the greater accuracy of the model.
REFERNCES:
Aczel,Amir D., Complete Business Statistics, 3rd Ed., Irwin/ McGraw-Hill
Bordens, Kenneth S. and Abbott, Bruce B. Research Design and Methods, A process Approach 4th Ed. Mayfield Publishing Company
Colander, David C., Economics, 3rd Ed. Irwin/
Geroski, P. A. and Gregg, G., Coping with Regression: Company Performance in
Adversity, Oxford University Press, co. 1997.
Larson, K, Miller, P., Financial Accounting, Irwin Press, London & N.Y., 1995
Sander, D. and Smidt, R., Statistics, A first course, sixth Ed. McGraw-Hill Higher
Eduction, co. 2000
Thomas, R.L. Modern Econometrics, An introduction Addison Wesley Longman co.1997
For further analysis ask sir_lander2004@yahoo.com.
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