This Book is intended to be textbook studied for undergraduate course in multivariate analysis. This book is designed to be used in semester system. In order to achieve the goals of the book, it is divided into the following chapters. Chapter One introduces matrix algebra. Chapter Two devotes to Linear Equation System Solution with quadratic forms, Characteristic roots & vectors. Chapter Three discusses Partitioned Matrices and how to get Inverse, Jacobi and Hessian matrices. Chapter Four deals with Multivariate Normal Distribution (MVN). Chapter Five concern with Joint, Marginal and Conditional Normal Distribution, independency and correlations. Many solved examples are intended in this book, in addition to a variety of unsolved relied pro

This Book is intended to be textbook studied for undergraduate course in multivariate analysis. This book is designed to be used in semester system. In order to achieve the goals of the book, it is divided into the following chapters. Chapter One introduces matrix algebra. Chapter Two devotes to Linear Equation System Solution with quadratic forms, Characteristic roots & vectors. Chapter Three discusses Partitioned Matrices and how to get Inverse, Jacobi and Hessian matrices. Chapter Four deals with Multivariate Normal Distribution (MVN). Chapter Five concern with Joint, Marginal and Conditional Normal Distribution, independency and correlations. Many solved examples are intended in this book, in addition to a variety of unsolved relied pro

Generally, direct measurement of soil compression index (Cc) is expensive and time-consuming. To save time and effort, indirect methods to obtain Cc may be an inexpensive option. Usually, the indirect methods are based on a correlation between some easier measuring descriptive variables such as liquid limit, soil density, and natural water content. This study used the ANFIS and regression methods to obtain Cc indirectly. To achieve the aim of this investigation, 177 undisturbed samples were collected from the cohesive soil in Sulaymaniyah Governorate in Iraq. Results of this study indicated that ANFIS models over-performed the Regression method in estimating Cc with R² of 0.66 and 0.48 for both ANFIS and Regre

In this paper we used frequentist and Bayesian approaches for the linear regression model to predict future observations for unemployment rates in Iraq. Parameters are estimated using the ordinary least squares method and for the Bayesian approach using the Markov Chain Monte Carlo (MCMC) method. Calculations are done using the R program. The analysis showed that the linear regression model using the Bayesian approach is better and can be used as an alternative to the frequentist approach. Two criteria, the root mean square error (RMSE) and the median absolute deviation (MAD) were used to compare the performance of the estimates. The results obtained showed that the unemployment rates will continue to increase in the next two decade

Variable selection in Poisson regression with high dimensional data has been widely used in recent years. we proposed in this paper using a penalty function that depends on a function named a penalty. An Atan estimator was compared with Lasso and adaptive lasso. A simulation and application show that an Atan estimator has the advantage in the estimation of coefficient and variables selection.

In this study, we investigate the behavior of the estimated spectral density function of stationary time series in the case of missing values, which are generated by the second order Autoregressive (AR (2)) model, when the error term for the AR(2) model has many of continuous distributions. The Classical and Lomb periodograms used to study the behavior of the estimated spectral density function by using  the simulation.

Competitive advantage is a substantial  strategic objective for organizations. It requires high levels in the quality of products and services provided to customers, continuous improvement of costing , care for creativity and innovative employees, and speed unique to the marketing and financial engineering, and business re-engineering processes. The situation in this area, requires actors to attract and develop human resources, including help in proper implementation of the strategic tasks that targeted by those institutions. According to the opinions and viewpoints of management scholars, the competitive advantage resource is the most important issue for organizations in the third millennium, which can be a

The researcher attempts to examine Barman model in acquiring the historical concepts among fourth-grade students at literary classrooms. To this end, the researcher held the null hypothesis, there is no significant difference between the experimental groups who was taught based on Barman model and the control group that taught based on the traditional method in acquiring the historical concepts on the post-test. To testify the effectiveness of Barman model, the researcher administered a questionnaire included (60) items on bunch of female-students who were selected from al-khamaeal preparatory school in al-hurriyah district in Baghdad. The author utilized different statistical tools to analyze the collected data.    &

Objective conditions for the possibility of punishment are legal or material facts –positive or negative that depart from the activity of the offender. The legislator comments on their subsequent verification on the formation of some crimes the possibility of.The application of punishment to the offender , but although they are facts of an object nature that approach and overlap with many systems and cases , they are distinguished by a certain subjectivity that differentiates them from each case that may seem similar or approach them. To clarify the ambiguity that may surround these conditions , Which may lead to confusion between them and what be similar to other cases due to the common effect that they have in common , which is the f

 Internet of Things (IoT) contributes to improve the quality of life as it supports many applications, especially healthcare systems. Data generated from IoT devices is sent to the Cloud Computing (CC) for processing and storage, despite the latency caused by the distance. Because of the revolution in IoT devices, data sent to CC has been increasing. As a result, another problem added to the latency was increasing congestion on the cloud network. Fog Computing (FC) was used to solve these problems because of its proximity to IoT devices, while filtering data is sent to the CC. FC is a middle layer located between IoT devices and the CC layer. Due to the massive data generated by IoT devices on FC, Dynamic Weighted Round Robin (DWRR)