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: The Ministry of Education-Kurdistan Regional Government (MOE-KRG) currently depends only on the students' grades in the evaluation of the teachers' performance level in all subjects as low, medium, or high performance. Relying just on one variable to determine teacher's performance is not fair and this problem must be resolved statistically throu...
There are many phenomena that require waiting lines and should be arranged in a proper way. To make decisions on determining hospital needs and resources, queuing theory is a helpful device for solving these problems. Therefore, queuing line in the CT scan unit in Erbil teaching hospital was taken into account to find queuing models for it and solv...
Classification of raw data through a frequency distribution is very important to determine the nature of the data distribution (probability distribution) and their structures. This paperdescribes the classifications of the number of verses (Ayas), words and letters in the chapters (Sura) of the Holly Quran using frequency distributions (tables) and...
The land of Kurds Nation famous with the name of Kurdistan divided into 4 parts located in 4 countries: Turkey, Iran, Iraq, and Syria. Many years ago, the ambition and aim of this nation is the independence of all 4 parts and nowadays the circumstances are very suitable for that but the problem is how to solve the major issues among the leaders...
This paper proposes a new improvement of the Nadaraya-Watson kernel non-parametric regression estimator and the bandwidth of this new improvement is obtained depending on universal threshold level with wavelet of kernel function instead of using fixed bandwidth and variable bandwidth for geometric, arithmetic mean, range and median measurements. A...
This research discusses the formation of four multivariate quality control charts to control the mean vector and variance matrix in two cases of multivariate t distribution and two cases of Generalized Multivariate Modified Bessel Distribution (GMMBD). This process is performed using Bayesian sequential method with State Space Model (SSM) through a...
The main purpose of this research is to construct a chart for controlling the mean and variance together of a data distributed multivariate t distribution using State Space Model (SSM) through applying Bayes' Factors (BF). The constructed control chart will undertake the case when parameters' vector is unknown and variance matrix is known. Then, dr...
В статье представлен статистический анализ структурных сдвигов в распределении объемов до" бычи и экспорта нефти и газа стран " членов ОПЕК с помощью линейных и квадратических коэффициентов абсолютных структурных сдвигов (цепные и базисные).
Представленный анализ запасов, добычи и экспорта сырой нефти и газа стран - членов ОПЕК раскрывает их стратегии и взаимоотношения, сегментацию экспортирующих и импортирующих стран мира на основе статистических методов.
Fingerprint recognition has attracted many researchers in order to conduct studies in this field. The need for finding an AFIS (Automatic Fingerprints Identification System) has been an interesting subject by scientists, bureaus and companies, because the increasing use of AFIS leads to solve many problems of identification, because there are no to...
I am doing a Multivariate Linear Regression Analysis in Psychometric research with a dependent variable that is calculated by averaging 12 Likert items (10 point-scale from 1 to 10 points) on 4 Likert scales (4 independent variables). When conducting a Multivariate regression analysis, I will get a very low R2 and non-significant model (ANOVA), what should I do?
I have a parameter estimation table (ordinal logistic regression) obtained from SPSS. How could convert estimated parameters table into equations (i.e. y1=b0+b1x1+b2x2, ...., y2=b0+b1x1, .....)?
I attached my table for more information
I have 3 variables with N=46.
I did normality test for each variable using Chi-squared test.
The degrees of freedom for each one is 3, 4, and 5, why?
I know that the d.f. in easy fit is equal to k=1+log2 (N).
They must be the same, where is the problem?
I have problem with negative forecasting values using ARIMAX in MATLAB although I revised my data and did the analyses many times with and without differences but the negative forecast values still present. Please your suggestion or any way to solve this problem?
1. Is there any tests for knowing the stationarity of a dynamic model (ARIMAX)?
2. In ARIMA models, we take first or second differnces to make the series stationary. But in ARIMAX, how we can take first or second differences to make the dynamic series stationary? Is it by taking differences for each variable separately (variable x alone, variable y alone also) or how?
I looked at the help of EasyFit and says "Please note that this test is available for continuous sample data only.". I know that I can use chi-square test for discrete data also! So, what is your comments on it?