Analysis of a number of climatic factors on the temperature in Duhok governorate for the period of time (1/2010 - 10/2017)
The focus of attention in this research will be focused on one of the advanced statistical methods, which is the multiple linear regression usually used to describe the relationship between variables, which includes the accuracy of statistical inference of the desired results of the research, as the research dealt with studying a number of climatic variables that were represented by (the proportion of snow, The amount of rain, wind speed and relative humidity) and their effect on temperatures, as the sample is a monthly average of 94 individuals taken from January 2010 until October 2017.
After the studied model was applied to the research sample, the results clarified that there is a statistically significant relationship between each of the variables (snow percentage, amount of rain and relative humidity) with the temperature variable, except for the wind speed variable, it has no statistical indication that it has a role in the changes taking place. In temperatures. After estimating the model that describes the relationship between the variables up to the most important stages on which the accuracy of the desired results of the estimated model is based, which is the stage of studying the residuals generated from it, which represents a fundamental step to consider its efficiency, the results reported that there is a problem of self-correlation for the rest of the estimated model in addition to that it does not follow Normal distribution, and this in itself is a problem and contrary to the assumptions of the least squares method used in estimation, and it cannot be left without reconsidering it. In order to reach the desired goal, which is to rid the remainder of the self-correlation problem, the variables were transformed by taking the time lag of the first degree for all the research variables, and then going back again to estimate the new model and examine the residuals associated with it. The efficiency of the estimated model, in addition, became tracking the normal distribution and thus this defect was eliminated, and this result is sufficient to accept the latest new model estimated as an optimal model for explaining the changes in the rise and fall of temperatures over the years, and it is possible to expect any value we want through this model Just assuming any given value for the independent variables.
1.1.6الرسائل والاطاريح الجامعية
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