USING RIDGE REGRESSION TO ESTIMATE SOME VARIABLES AFFECTING THE IRAQI STOCK EXCHANGE INDEX

Ridge regression method is one of the most widely used methods for solving the multicollinearity problem as an alternative to the Ordinary Least Squares (OLS) when there is a collinearity between the explanatory variables, the presence of multicollinearity will produce unreliable result in the estimates of the parameters of OLS. Due to such a reason, this study aims to use the new version of the ridge regression to estimate the coefficients of some important economic variables as a real application. A numerical example of stock market index and macroeconomic variables in Iraq is employed using both methods aimed at to investigate the relationship of the variables in the presence of multicollinearity in the data set. The variables of interest are the index of Iraqi Stock Exchange (ISE), the Prices of Crude Oil (POC) and Gold (POG), and the Global Inflation Rates (GIR). Depending on the mean squares error criterion, the results show that the new version of the ridge regression procedure is able to estimate the model and produce reliable results by reducing the effect of multicollinearity in the data set

THE EFFECT OF SOME MACROECONOMIC VARIABLES ON STOCK MARKET MOVEMENT IN IRAQ

Regarding the effect of macroeconomic variables such as money supply and interest rate on stock prices, the efficient market hypothesis suggests that competition among the profit-maximizing investors in an efficient market will ensure that all the relevant information currently known about changes in macroeconomic variables are fully reflected in current stock prices, some of these relevant information (explanatory variables) may have interrelation (collinearity). In regression analysis, multicollinearity refers to a high strength correlation among the explanatory variables. Thus, the ordinary least squares (OLS) are unreliable because of the violation of the independence assumption of the explanatory variables. The high dependency in explanatory variables will cause huge value in the standard errors of parameter estimates and thus, OLS is no longer appropriate to be employed in modeling the data. The most popular method used to overcome this problem is ridge regression. A numerical example of stock market price and macroeconomic variables in Iraq is employed using both methods to investigate the relationship of the variables in the presence of multicollinearity in the data set. The variables of interest are consumer price index (CPI), gross domestic product (GDP), base lending rate (BLR), and money supply (M1). The obtained findings show that the ridge regression method can estimate the model and produce reliable results by reducing the effect of multicollinearity in the data set. It is concluded that there is a relationship between macroeconomic variables (CPI, GDP, BLR and M1) and stock prices in the Iraqi stock market ISE, and that these variables account 98.5% of the change in ISE

Using Particle Swarm Optimization to Determine the Optimal Strata Boundaries

Stratified random sampling is a commonly used sampling methodology especially for heterogeneous populations with outliers. Stratified sampling is preferably employed due to its capability of improving statistical precision by yielding a smaller variance of the estimator, compared with simple random sampling. In order to reduce the variance of the estimator in stratified sampling, the problems of stratum boundary determination and sample allocation must be resolved initially. This paper proposes a PSO algorithm to solving the problem of stratum boundary determination in heterogeneous populations while distributing the sample size according to Neyman allocation method. The PSO algorithm is tested on two groups of populations and a comparative study with Kozak, GA and Delanius and Hodges methods have been implemented. The numerical results show the ability of the proposed algorithm to find the optimal stratified boundaries for a set of standard populations and various standard test functions compared with other algorithms

Factors Affecting Number of Born Children in Iraq

Background: This paper investigates the factors that are associated with the effect of the number of born children in Iraq. Methods: In this work, we aim to determine the contributing factors that affect the number of born children. Multiple and simple linear regression models together with two-sample t-tests were conducted to verify the potential risk factors that affect the born children which include but are not limited to smoking mother, mother age, a mother with the thyroid gland, mothers that use the medicine, preterm birth (PTB), low birth weight (LBW), high birth weight (HBW), and small for gestational age (SGA). The most important aspects of this study are investigating maternal and paternal factors affecting the number of born children in Iraq. Analyzing and identifying the risk factors that affect the number of born children and those factors that do not the number of born children are part of the contribution. Results: The multiple regression model predicted that the maternal factors like mother weight ( ), smoking medicine ( ) with (p ≤ 0.05, p ≤ 0.05, p ≤ 0.05, p ≤ 0.05, p ≤ 0.05, p ≤ 0.05) respectively were significantly associated with the effect of the number of born children, while the mother age ( and husband age ( with (p 0.05, and p 0.05) respectively were not significant. Regarding the two-sample t-tests, the first analysis suggested that the smoking mothers significantly affected the number of born children with (p ≤ 0.05). The second analysis shows that the mediation effect of the thyroid gland was not significant with (p 0.05). The third analysis patterning the medicine of the mother did not significantly affect the number of birth children with (p 0.05). Conclusion: The results obtained from this work predicted that smoking mothers strongly contributed and play a vital role toward the factors affecting the number of born children, these findings would tackle and reduce the higher risk associated with factors that affect the number of born children in Iraq. Most of the existing literature focused on paternal risk factors affecting birth outcomes, while others were restricted to single maternal factors associated with child outcomes. In this study, we thoroughly investigate several maternal factors affecting the number of born children and paternal factors as well

Access to and Utilization of Information and Communication Technology by the Teaching Staff at Tishk International University

The objective of this study is to assess the usage of Information and Communication Technologies (ICT) by TISHK International University (TIU) teaching staff. The data were obtained from 62 teaching staff from the Engineering, Information Technology (IT) and Education faculties. A standardized questionnaire was utilized to obtain data from research participants. Descriptive statistics, Confidence Interval, One-Sample t-test, Two-Sample t-test, and one-way ANOVA were all used to analyse the data obtained. This facilitated the evaluation of differences in usage by various departments and faculties at the university. The outcome of the study was that there were no differences in usage of ICT regarding the participants’ educational status, ages, gender, educational level, and marital status. However, a significant difference in the number of hours spent using ICT tools was found

Using Linear Regression Analysis to Study the Recovery Cases of COVID 19 in Erbil, Kurdistan Region

This paper studies the statistical analysis of COVID 19 in Erbil, Kurdistan region by considering multiple regression model. we present the details analysis of COVID 19 in Erbil, Kurdistan using statistical model (multiple regression analysis). The regression model is used to predict the recovery cases of COVID 19 in Erbil, Kurdistan. Based on our findings from the regression model, we observed a significant difference in the regression coefficient of the model. Also, the higher the number of test patient leads to the higher number of recovery patient, moreover, there is a lesser effect in the recovery rate compared with the fatality cases. Lastly, we came up with some suggestions that will curb the spreading of COVID 19, increase the number of recovery cases, control the higher number of death cases, and prevent the future occurrence of COVID 19 in Erbil, Kurdistan region

FACTORS AFFECTING THE MOTIVATION OF STUDENTS SPEAKING SKILLS’ PROGRESS

Speaking skill is of great importance to English language learners. As is known, motivation plays an important role in the development of speaking skills. Motivation, in turn, is also affected by other variables. This study aims to analyze the factors that influence learners’ motivation. The analysis was carried out using five variables, namely, motivation, personality, attitudes towards English language teachers, classroom environment and instructional media, and attitudes towards English language. Data collection method included a questionnaire distributed to the participant of this study which included 92 participants from Tishk International University (TIU) studying in education, pharmacy, nursing, and medical analysis faculties. From this research, it is concluded that the variables that have the most influence on learners’ motivation are attitudes towards English language teachers, classroom environment and instructional media, and attitudes towards English language, where these variables have a positive effect on learners’ motivation

Approximate Methods to Obtain the Optimum Stratum Boundaries: A Comparative Study

In this article, we shall present an approximately optimal method for constructing stratum boundary points when the sample is allocated proportionally. The method is based on an equal partitioning of the cumulative f^(6⁄(7 )), where f is the distribution of the stratification variable. We show that in many practical situations, this technique compares favorably with approximately optimal stratification and allocation methods of previously suggested

Investigating the Causes of the Decline in Mathematics Performance Among High School Students in Iraq: A Teacher\'s Perspective.

Recent studies indicate that mathematics performance by high school students in the Iraq have declined considerably. There are many reasons that have been advanced for this phenomenon, chief among them, the political turmoil the country has gone through in the recent past. This paper endeavoured to find out specific reasons that teachers perceive to be causing such decline in performance. Data was collected from teachers in 8 major cities of Iraq through an online questionnaire. The results show that mathematics curriculum, lack of proper grounding in the foundation years, lack of concentration among students during lesson time and overcrowding in the classroom contribute to demotivation of students in mathematics leading to poor performance

Understanding Challenges of Mathematics Education in Iraq: A Focus on Kurdistan Region

Mathematics is stereotyped as a ‘difficult’ subject in many parts of the world, and many other stereotypes about the subject abound. This study, therefore, determined and examined some of the psychological barriers to mathematics education that could be responsible for driving such stereotypes in Kurdistan region, Iraq. A questionnaire was used to collect data from students in five departments of the faculty of education at an International University in Kurdistan, Iraq and analysed through SPSS and Minitab. Results confirmation lack of self-confidence, anxiety, and attitude toward mathematics as some of the psychological barriers to mathematics for students in the region. The study further corroborated the assertion that teachers play a key role in influencing students’ attitudes toward mathematics but have a negligible or no role in enhancing students’ self-confidence in mathematics in the region. Additionally, attitude is shown to have a strong negative relationship with anxiety and self-confidence. Suggestions and recommendations to improve the situation are outlined in the paper