It is well-known that the existence of outliers in the data will adversely affect the efficiency of estimation and results of the current study. In this paper four methods will be studied to detect outliers for the multiple linear regression model in two cases : first, in real data; and secondly, after adding the outliers to data and the attempt to detect it. The study is conducted for samples with different sizes, and uses three measures for comparing between these methods . These three measures are : the mask, dumping and standard error of the estimate.
Background: Non-atherosclerotic spontaneous coronary artery dissection (SCAD) is defined as a non-traumatic and non-iatrogenic separation of the coronary arterial wall. SCAD is a highly uncommon cause of myocardial infarction (0.1 to 0.4 %).
Case presentation: 40-year-old African American woman, G1T1P0A0L2, with a past medical history of tobacco abuse and obesity who had uncomplicated cesarean section delivery for healthy twins two weeks prior presented with substernal, sudden onset chest pain. The pain radiated to left arm and back, pressure-like, and is associated with nausea, vomiting, and dyspnea.
On examination she was within normal limits except for a well-healed C-section wound. An electrocardiogr
... Show MoreLinear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.
In this paper we have been focus for the comparison between three forms for classification data belongs
... Show MoreBackground: Multiple sclerosis is a chronic heterogeneous demyelinating axonal and inflammatory disease involving the Central Nervous System [CNS] white matter with a possibility of gray matter involvement in which the insulating covers of nerve cells in the brain and spinal cord are damaged. This damage disrupts the ability of parts of the nervous system to communicate, resulting in a wide range of signs and symptoms. Cerebral venous insufficiency theory was raised as a possible etiology for the disease at 2008 by Zamboni an Italian cardiothoracic surgeon. This theory was defeated by Multiple Sclerosis[ MS] researchers and scientists who thought that the disease is an autoimmune rather than vascular.
Obj
... Show MoreObjectives: To Assess the Effect of Physical Status of Polycystic Ovarian Syndrome on Women in Reproductive Age,
To Find out the Relationship Between Polycystic Ovarian Syndrome and Women's Physical Health (Acne , Hirsutism ,
Weight Gain , Irregular Menstrual Period),&To Identify the Association of Physical Status to polycystic ovarian
syndrome and Some Socio Demographic Characteristic (Age ,Occupation & Obesity ), and Reproductive
Characteristic(Gravida ,Para ,Abortion &Menstrual Regularity).
Methodology :a descriptive analytical study was conduct on Non-probability (purposive sample) of (100)women who
suffering from polycystic ovarian syndrome in reproductive age in infertility counseling from three hospit
The current study aims to identify the organizational values of kindergarten teachers as well as to identify the difference in the organizational values of kindergarten teachers in term of years of service, to do this; the researcher designed a scale to measure the organizational values. The scale was applied on a sample of (400) kindergarten teachers. The resesults revealed that kindergarten teachers have a high level of organizational values within the classroom. The result of the second objective showed significant differences among the organizational values (political,
... Show MoreIn this paper, a new technique is offered for solving three types of linear integral equations of the 2nd kind including Volterra-Fredholm integral equations (LVFIE) (as a general case), Volterra integral equations (LVIE) and Fredholm integral equations (LFIE) (as special cases). The new technique depends on approximating the solution to a polynomial of degree and therefore reducing the problem to a linear programming problem(LPP), which will be solved to find the approximate solution of LVFIE. Moreover, quadrature methods including trapezoidal rule (TR), Simpson 1/3 rule (SR), Boole rule (BR), and Romberg integration formula (RI) are used to approximate the integrals that exist in LVFIE. Also, a comparison between those methods i
... Show MoreIn this paper two ranking functions are employed to treat the fuzzy multiple objective (FMO) programming model, then using two kinds of membership function, the first one is trapezoidal fuzzy (TF) ordinary membership function, the second one is trapezoidal fuzzy weighted membership function. When the objective function is fuzzy, then should transform and shrinkage the fuzzy model to traditional model, finally solving these models to know which one is better
Background: Assessment is an important part of the learning cascade in education. Students realize it as an influential motivator to direct and guide their learning. The method of assessment determines the way the students reach high levels of learning. It has been documented that one of factor affecting students’ choice of learning approach is the way how assessment is being performed. Many methods of assessment namely multiple choice questions, essay questions and others are mainly used to assess basic science knowledge in undergraduate education. Objectives: The aim of this study is to compare multiple choice questions (MCQ) and essay questions (EQ) (record the success and failure rate of multiple choice questions (MCQ) and essay quest
... Show MoreThe Dagum Regression Model, introduced to address limitations in traditional econometric models, provides enhanced flexibility for analyzing data characterized by heavy tails and asymmetry, which is common in income and wealth distributions. This paper develops and applies the Dagum model, demonstrating its advantages over other distributions such as the Log-Normal and Gamma distributions. The model's parameters are estimated using Maximum Likelihood Estimation (MLE) and the Method of Moments (MoM). A simulation study evaluates both methods' performance across various sample sizes, showing that MoM tends to offer more robust and precise estimates, particularly in small samples. These findings provide valuable insights into the ana
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