Determining the best method to detect and remedy heterocedasticity of multiple linear regression by Appling in simulation data
Hessain Adam Hessain Iydam, Afra Hashim Abdelateef Mohammed
Constructing an econometric model fit for forecasting necessarily requires that it be free from measurement problems. This research paper focused on the problem of Heterocedasticity by comparing common detection methods and remedies applied to simulated model was data is corresponding to the government expenditure. The descriptive and analytical approach used is statistical packages (SPSS V.20) and (E. Views V.9) and (Excel v.10), and the most important results after applied in Simulated data was that the best test led to the detection of Heterocedasticity is White's Test, based on the determination coefficient and the probability value, which proved its advantage in helping to detect the problem when applied in the simulated model and the remedies. The best remedy that led to the detection of the problem was the first remedy because it was proven that 6 out of the 8 detection methods led to the remedy, followed by the third and fifth (by using logarithm) Assumptions. It was proven that 5 out of the 8 detection methods led to the remedy. The paper recommended using the White's Test to detect the problem of Heterocedasticity and remedy by taking algorithms.