Share
استعمال اساليب التنبؤ الاحصائية في تحليل قيم الصادرات النفطية == Using Statistical Forecasting Methods In Analyzing Oil Exports Values
Author name:
لينا نضال شوكت
Supervisor name:
قتيبة نبيل نايف القزاز
General topic:
Administration and Economics
Specific topic:
Statistics
Degree:
Higher Diploma
University:
University of Baghdad - Faculty Of Administration And Economics - Department Of Statistics
Language:
Arabic
University location:
Baghdad
First pages:
07T3989 - p.pdf
Abstract:
درست الباحثة موضوع اقيام الصادرات النفطية العراقية السنوية وللمدة من 1978م ولغاية 2014م بالاعتماد على ثلاث طرائق تحليل احصائية. الاولى، تحليل انموذج الانحدار الخطي المتعدد والتي تتطلب تحديد متغيرات توضيحية مؤثرة في قيم الصادرات النفطية وكانت هذه المتغيرا | The researcher studied the Iraqi Oil Exports Value form 1978 until 2014 using three statistical analysis methods. The first, Analysis of Multiple Linear Regression which requires determining independent variables that affect the Oil Exports Value and these variables were (barrel price and the average daily number of exported barrels). The second, Analysis of Polynomial Models (Growth Curve Model) and this model requires determining the suitable polynomial degree to represent the model as a curve which shows the increase or decrease that occurs in the data under study. And the third method is, Analysis of Time Series using Box - Jenkins models which requires identification of the suitable model and the degree of the model to represent the data. The three models, their equations and the mathematical relationships have been all defined, especially the ones that have been applied on the data.After analyzing the data using gretl and Matlab softwares and treating some problems that may occur to the data and getting the suitable models to represent the Oil Exports Value, in the Multiple Regression Model the confidence intervals of the estimated parameters have been calculated and testing the efficiency of the model and the estimated parameters using F and t tests. And in the Polynomial model, the curve has been estimated and drawn and calculating the confidence intervals of the parameters and the fitted curve and forecasting for 6 coming years and calculating the confidence intervals of the forecasting. In the Time Series model, the stationarity in the mean and variance of the series has been tested then identifying the suitable order for the model which was (2,1,3) and testing the independence of the error then forecasting for 6 coming years and calculating the confidence intervals of the forecasting
