An Overview of Equal Educational Opportunities in Turkey: A Spatial Analysis of Classrooms in Rural and Urban Primary Schools

The number of students in a class is a primary factor affecting the quality of education. Therefore, this study examines the distribution of the number of students per class in rural and urban primary schools in Turkey, and efforts have been made to specify classroom needs. Statistical data was obtained from the Turkish Institute of Statistics and the Ministry of National Education. In order to better interpret data, graphs and maps were prepared with the help of GIS. The MapInfo 12.0 program was used for map drawing. The data was mapped using the Inverse Distance Weighted Algorithm. Whether there was global clustering regarding the distribution of the number of students per class in both rural and urban primary schools in Turkey was investigated using Moran I. In addition, local Moran I maps were employed to identify whether or not there was local clustering or neighboring interaction. At the end of the research, a variety of findings and results were obtained regarding the condition of primary school classes in Turkey. In conclusion, it has been determined that there is a need for more classes in certain regions, while they are urgently needed in others

Estimating Variances in Weighted Least-Squares Estimation of Distributional Parameters

Many estimation methods have been proposed for the parameters of statistical distribution. The least squares estimation method, based on a regression model or probability plot, is frequently used by practitioners since its implementation procedure is extremely simple in complete and censoring data cases. However, in the procedure, heteroscedasticity is present in the used regression model and, thus, the weighted least squares estimation or alternative methods should be used. This study proposes an alternative method for the estimation of variance, based on a dependent variable generated via simulation, in order to estimate distributional parameters using the weighted least squares method. In the estimation procedure, the variances or weights are expressed as a function of the rank of the data point in the sample. The considered weighted estimation method is evaluated for the shape parameter of the log-logistic and Weibull distributions via a simulation study. It is found that the considered weighted estimation method shows better performance than the maximum likelihood, least-squares, and certain other alternative estimation approaches in terms of mean square error for most of the considered sample sizes. In addition, a real-life example from hydrology is provided to demonstrate the performance of the considered method

On the performance of the flexible maximum entropy distributions within partially adaptive estimation

The partially adaptive estimation based on the assumed error distribution has emerged as a popular approach for estimating a regression model with non-normal errors. In this approach, if the assumed distribution is flexible enough to accommodate the shape of the true underlying error distribution, the efficiency of the partially adaptive estimator is expected to be close to the efficiency of the maximum likelihood estimator based on knowledge of the true error distribution. In this context, the maximum entropy distributions have attracted interest since such distributions have a very flexible functional form and nest most of the statistical distributions. Therefore, several flexible MaxEnt distributions under certain moment constraints are determined to use within the partially adaptive estimation procedure and their performances are evaluated relative to well-known estimators. The simulation results indicate that the determined partially adaptive estimators perform well for non-normal error distributions. In particular, some can be useful in dealing with small sample sizes. In addition, various linear regression applications with non-normal errors are provided.Partially adaptive estimator Maximum entropy distribution Efficiency Non-normal error term

Lojistik Regresyon ve Perseptron Modelleri Kullanılarak Rüzgar-Günes Enerji Santral Modellerinin Güç Üretim Analizinin Durumu

Bu çalısmada, Anadolu Üniversitesi iki Eylül Kampusu 'nde kurulmus olan hibrit (rüzgar-günes) enerji santral modelinin, rüzgar hızı, günes ısınım siddeti, izlenen saat verilerine dayalı olarak belirlenen günlük yük talebini karsılayacak enerji üretip üretmeyecegi lojistik regresyon modelleri olan logit ve probit regresyon ve tek katmanlı perseptron kullanılarak sınıflandırılmıstır. Yapılan analizler sonucunda logit ve probit regresyon modellerinin yaklasık %87 dogruluk oranıyla, perseptronun ise yaklasık olarak %70 dogruluk oranıyla sistemin çalısma durumunu tespit ettigi görülmüstür

A Monte Carlo simulation study on partially adaptive estimators of linear regression models

This paper presents a comprehensive comparison of well-known partially adaptive estimators (PAEs) in terms of efficiency in estimating regression parameters. The aim is to identify the best estimators of regression parameters when error terms follow from normal, Laplace, Student's t , normal mixture, lognormal and gamma distribution via the Monte Carlo simulation. In the results of the simulation, efficient PAEs are determined in the case of symmetric leptokurtic and skewed leptokurtic regression error data. Additionally, these estimators are also compared in terms of regression applications. Regarding these applications, using certain standard error estimators, it is shown that PAEs can reduce the standard error of the slope parameter estimate relative to ordinary least squares.

THE COMPARATIVE ANALYSIS OF TWO DIFFERENT STATISTICAL DISTRIBUTIONS USED TO ESTIMATE THE WIND ENERGY POTENTIAL

In this paper, the wind energy potential of the region is analyzed with Weibull and Reyleigh statistical distribution functions by using the wind speed data measured per 15 seconds in July, August, September, and October of 2005 at 10 m height of 30-m observation pole in the wind observation station constructed in the coverage of the scientific research project titled "The Construction of Hybrid (Wind-Solar) Power Plant Model by Determining the Wind and Solar Potential in the Iki Eylul Campus of A.U." supported by Anadolu University. The Maximum likelihood method is used for finding the parameters of these distributions. The conclusion of the analysis for the months taken represents that the Weibull distribution models the wind speeds better than the Rayleigh distribution. Furthermore, the error rate in the monthly values of power density computed by using the Weibull distribution is smaller than the values by Rayleigh distribution

Statistical Analysis Of Wind Speed And Power Densities Using Weibull Distribution

Weibull olasılık yoğunluk fonksiyonu, rüzgar enerjisi potansiyelini belirlemede en çok kullanılan istatistiksel dağılımlardan biridir. Ortalama rüzgar hızı, ortalama rüzgar gücü yoğunluğu ve dolayısıyla rüzgar enerjisi tahmini genellikle iki parametreli Weibull olasılık yoğunluk fonksiyonuna dayalı olarak yapılmaktadır. Bu çalışmada, yürütülen Bilimsel Araştırma Projesi kapsamında Anadolu Üniversitesi İki Eylül Kampüsü ‘ndeki 2005 yılı Temmuz, Ağustos, Eylül ve Ekim aylarında 15 sn aralıklarla ölçülen rüzgar hızı verilerine dayanarak, rüzgar hızı ve gücünün ele alınan aylara göre değişimleri, parametreleri Moment Metoduyla bulunan Weibull dağılımı yardımıyla incelenmiştir. Böylece, genel anlamda Eskişehir bölgesinin rüzgar enerji potansiyelinin belirlenmesi için bir ön çalışma yapılmıştır.Weibull probability density function is one of the most widely used statistical distributions that are used to determine the wind energy potential. Average wind speed, average wind power and average wind energy, which is a direct result of these two, is generally forecasted using two-parameter Weibull power density function. In this study, which is covered under a Scientific Research Project of Anadolu University, the changes in the wind speed and power in 2005 July, August, September and December in Iki Eylul Campus of Anadolu University are studied using Weibull distribution that is found with the help of parameters using Moment Method. Consequently, a preliminary research for the the wind energy potential of Eskisehir region is completed

RÜZGAR ENERJİSİ POTANSİYELİNİN TAHMİNİNDE KULLANILAN İKİ FARKLI İSTATİSTİKSEL DAĞILIMIN KARŞILAŞTIRMALI ANALİZİ

Bu çalışmada, Anadolu Üniversitesi tarafından desteklenen "A. Ü. İki Eylül Kampusu'nda Rüzgar ve Güneş Potansiyelini Belirleyerek Hibrid (Rüzgar-Güneş) Enerji Santral Modeli Kurmak" başlığı altındaki bilimsel araştırma projesi kapsamında kurulan rüzgar gözlem istasyonundaki 30 metrelik ölçüm direğinin 10 metre yüksekliğinden 2005 yılı Temmuz, Ağustos, Eylül ve Ekim aylarında 15 sn aralıklarla ölçülen rüzgar hızı verileri kullanılarak Weibull ve Rayleigh istatistiksel dağılım fonksiyonları ile bölgenin rüzgar enerjisi potansiyeli analiz edilmiştir. Bu dağılımların parametrelerinin bulunmasında Maximum Likelihood Metodu kullanılmıştır. Ele alınan aylar için yapılan bu analizler sonucunda, Weibull dağılımının Rayleigh'e göre rüzgar hızını daha iyi modellediği görülmüştür. Ayrıca, Weibull dağılımından hesaplanan aylık güç yoğunluğu değerlerindeki hata oranı, Rayleigh dağılımından hesaplanan değerlere oranla daha küçük çıkmıştır