In this research, we discussed and analyzed the relationship between oil prices and the U.S. dollar exchange rate in Iraq. The study adopted the descriptive analysis and econometrics analysis. The descriptive analysis refers to the rise (fall) in crude oil price lead to appreciate (depreciate) in the Iraqi dinar exchange rate, though the channel of the international reserves. The econometrics analysis is based on monthly data covered the period (December/2002 – December/2011), the unit root test, co-integration test, vector error correction model, and Granger causality test have been adopted in this research to check the existence and direction of this relationship. The results refer to the lon

The research aims to prepare a report by the external auditor (Federal Office of Financial Supervision) for the control environment it is includes financial control, commitment and performance of the North Oil Company (extractive) according to the causes of pollution. The research problem it is not the Federal Office of Financial Supervision preparation a report on the things the environment include the prevent or reduction failure the administration of the causes of the pollution caused by oil mining industry by both bad planning or operational or related to efficient human resources as well as of technology to use and resulting from non-compliance local laws and instructions, as well as the inefficiency of spending on environme

Due to the lack of statistical researches in studying with existing (p) of Exogenous Input variables, and there contributed in time series phenomenon as a cause, yielding (q) of Output variables as a result in time series field, to form conceptual idea similar to the Classical Linear Regression that studies the relationship between dependent variable with explanatory variables. So highlight the importance of providing such research to a full analysis of this kind of phenomena important in consumer price inflation in Iraq. Were taken several variables influence and with a direct connection to the phenomenon and analyzed after treating the problem of outliers existence in the observations by (EM) approach, and expand the sample size (n=36) to

Abstract

      Oil is the most important natural resources in Iraq and represents the goal to others as well as Iraqi people. It is gift from God to all Iraqi people now and future. So we must maintain it and invest its revenue that achieve development in country and ensure the next generations' rights in it without external costs or negative externalities from extracted and invested it.

    The most problems that we attempt to solve by this research are the exhausted, environmental degradation and theft from next generation that produced with oil contracts between Iraq and foreign companies. From here was th

Statistical methods of forecasting have applied with the intention of constructing a model to predict the number of the old aged people in retirement homes in Iraq. They were based on the monthly data of old aged people in Baghdad and the governorates except for the Kurdistan region from 2016 to 2019. Using BoxJenkins methodology, the stationarity of the series was examined. The appropriate model order was determined, the parameters were estimated, the significance was tested, adequacy of the model was checked, and then the best model of prediction was used. The best model for forecasting according to criteria of (Normalized BIC, MAPE, RMSE) is ARIMA (0, 1, 2)

Statistical methods of forecasting have applied with the intention of constructing a model to predict the number of the old aged people in retirement homes in Iraq. They were based on the monthly data of old aged people in Baghdad and the governorates except for the Kurdistan region from 2016 to 2019. Using Box-Jenkins methodology, the stationarity of the series was examined. The appropriate model order was determined, the parameters were estimated, the significance was tested, adequacy of the model was checked, and then the best model of prediction was used. The best model for forecasting according to criteria of (Normalized BIC, MAPE, RMSE) is ARIMA (0, 1, 2).

Abstract

That Iraq's dependence on the revenues of the oil product in financing its development programs and growth rates , Making the economy affected by external forces represented by fluctuations in crude oil prices in the global market, Which is directly reflected on the performance and efficiency of the Iraqi economy.

The study adopted its objectives to analyze the time series for the period (1988 - 2015) through the use of standard and statistical methods, Four standard models were estimated to reach those targets, Where the results of the stability test showed instability of most variables at their original level, But to achieve stability when taking the first differences, While the result

In this research ,we will study the phenomenon of dust storms for all types
(Suspended dust , rising dust , dust storm) , and its relationship with some climate
variables (Temperature , rainfall ,wind speed , Relative humidity ) through
regression models to three different locations ( Kirkuk , Rutba , Diwaniya ) almost
covering Iraq area for the period (1981 – 2012) . Time series has been addressing the
phenomenon of storms and climate variables for the time period under study to
attain the best models for long range forcast to the dust storms.

In this work, linear and nonlinear optical properties of two types of Iraqi heavy crude oil extracted from fields in southern Iraq were determined. The nonlinear optical properties were measured utilizing Z-scan technology with He-Ne laser at 632.8 nm. It was found that nonlinear refractive index (NLR) values for the Basra and Kut heavy crude oil samples are 6.34381×10^-4  and 8.25108×10^-4  cm²/mW, respectively, while those for the nonlinear absorption coefficient (NLA) are 2.68942×10^-5  and 2.58874×10^-5 , respectively. These results showed that the two samples with linear and nonlinear optical properties can be used in optics field applications as

Oil price forecasting has captured the attention of both researchers and academics because of the unique characteristics of crude oil prices and how they have a big impact on a lot of different parts of the economic value of the product. As a result, most academics use a lot of different ways to predict the future. On the other hand, researchers have a hard time because crude oil prices are very unpredictable and can be affected by many different things. This study uses support vector regression (SVR) with technical indicators as a feature to improve the prediction of the monthly West Texas Intermediate (WTI) price of crude oil. The root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) measur