This research paper is about thevariationin the degree of Continentality climate of the
Iraq during (40) years for a number of climate station. Using Poresof formula, it is found out
that the climate of Iraq ranges between extreme Continentality and very extreme
Continentality, and that the Continentality degree is characterized with extreme frequency
from one year to another. In certain years, the degree of climate Continentality decreases
while in other years it rises in such a way that there is no similarity in the Continental degree
from one year to another for the same station.
As for the general trend of the degree of Continentality, the last years had noticed
special variations, which are divided in to three climate regions: the first region exists in the
North and North-East of the country in which the Continentality degree tended to decrease
and it is ranged between-0.2% to -0.6%,while the Continentality degree of the second region,
which is located in the middle and north of the country, tended to rise simply and this ranged
between 0.6% to 1.7%. Finally, the Continentality degree of the third region, which is located
in the south-east tended to a most clear rise which ranged between 2.5% to 8.7%.
By drawing maps of the annual Continentality degree, it is found out that in some
yearsthe area of the extreme Continentality climate and the very extreme Continentality
climate are equal, while in other years, the area of the extreme Continentality climate
becomes much wider and the opposite happens in other years.
Linear regression is one of the most important statistical tools through which it is possible to know the relationship between the response variable and one variable (or more) of the independent variable(s), which is often used in various fields of science. Heteroscedastic is one of the linear regression problems, the effect of which leads to inaccurate conclusions. The problem of heteroscedastic may be accompanied by the presence of extreme outliers in the independent variables (High leverage points) (HLPs), the presence of (HLPs) in the data set result unrealistic estimates and misleading inferences. In this paper, we review some of the robust
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The results were analyzed and examined the hypothesis through a group of statistical methods. The most important results is the positive evaluation of the ba
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