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In this study, it is aimed to examine the relationship between students' statistical self-efficacy beliefs and their attitudes towards statistics and to propose a structural equation model by identifying the factors affecting them. IBM SPSS and AMOS package program were used in the data analysis. Data were collected from 330 university students who took statistics and biostatistics lessons to form the sample of the study. As a result of the analysis, it was concluded that the self-efficacy beliefs and attitudes towards to statistics lesson of students were at a moderate level. A positive and significant correlation was obtained between statistical self-efficacy belief and attitude. It was determined that statistical attitude explains 33% of the statistical self-efficacy belief. We propose to use modified multi-factor first-order and multi-factor first-order models for statistical self-efficacy belief and attitude levels, respectively. This result was supported with the values of goodness of fit indices.

This study is aimed to obtain an appropriate logistic regression model based on the bootstrap methods. For this purpose, two bootstrap methods called bootstrap I and bootstrap II are given to obtain the estimations of parameters and standard errors. Traditional logistic regression is compared with the bootstrap I and bootstrap II methods in terms of the parameter estimations and standard errors. It has been found that the standard errors of the parameter estimations for the bootstrap I model are smaller than others. Also, the average widths of confidence interval based on bootstrap I model are narrower than the logistic regression and bootstrap II. It is seen that, the simulation study based on different sample sizes supports these results. It can be said that the bootstrap I model based on resampling of errors term is the best in estimating coronary artery disease.

In this study,the performance of Nakagami distribution which is previously not used in themodel of siesmic data is compared with known Generalized extreme value, Gumbel,Weibull distributions. The comparison criterion is the coefficient ofdetermination and root mean square error. The siesmic magnitude data areanalyzed separately and maximum siesmic magnitudes are obtained for each yearand also block maxima (annual maximums) data set is determined. Considering thedata obtained in the short periods with extreme value theory in the study,long-term probability of an earthquake has been obtained. Parameter estimationsof the distributions fitted to the siesmic data and the variance-covariancematrices of these parameter estimates were determined. According to the coefficientof determination and root mean square error, it is determined that Nakagamidistribution is also as successful as other known distributions in themodelling of siesmic data. On the other hand; the fitting to the observedsiesmic data of the Gumbel distribution is revealed and return levels based onthis distribution is estimated. Thus, the probability of having an earthquakeof 5.1 is determined as 10% in the next 10 years., Bu çalışmada,deprem verilerinin modellemesinde daha önce kullanılmamış olan Nakagamidağılımının performansı, bilinen Genelleştirilmiş uç değer değer, Gumbel,Weibull dağılımları ile karşılaştırılmıştır. Karşılaştırma kriteri olarakbelirleme katsayısı ve hata kareler ortalamasının karekökü ele alınmıştır.Deprem büyüklüğü verileri ayrı ayrı incelenerek her bir yıl için maksimumdeprem büyüklükleri elde edilmiş ve blok maksima (yıllık maksimumlar) veri setibelirlenmiştir. Çalışmada uç değer teorisi ile kısa periyotlarda elde edilenveriler göz önünde bulundurularak, uzun periyotlarda deprem olma olasılıklarıelde edilmiştir. Deprem verilerine uydurulan dağılımların parametre tahminlerive bu parametre tahminlerinin varyans-kovaryans matrisleri belirlenmiştir.Belirleme katsayısı ve hata kareler ortalamasının karekökü değerlerine göre,deprem verilerinin modellemesinde Nakagami dağılımının da bilinen diğerdağılımlar kadar başarılı olduğu görülmüştür. Diğer yandan; Gumbel dağılımınıngözlenen deprem verilerine uyumu ortaya çıkarılarak bu dağılıma dayalıtekrarlama seviyeleri tahmin edilmiştir. Böylece, önümüzdeki 10 yıl içinde 5.1şiddetinde deprem olma olasılığının % 10 olduğu belirlenmiştir.

In random experiments, most analyses are based on interpretation of the difference between the means of experiment and control groups. Therefore, studying the difference between the variances of the experiment and control groups may also be useful in interpreting the analysis results. This study focuses on interval estimation with sample variance estimators based on Winsorized Mean and Trimmed Mean for the difference of the variances of two nonnormal populations. In the simulation study, confidence intervals based on robust estimators for the difference of the variances of two non-normally distributed populations were compared in terms of coverage probabilities and average length widths. According to simulation study, it was determined that the coverage probabilities of confidence intervals based on robust estimators were very close to the nominal confidence level in any case. However, it was seen that the average length widths of confidence intervals obtained with sample variance estimator based on Trimmed Mean were narrower compared to the average length widths of confidence intervals obtained with sample variance estimator based on Winsorized Mean. In addition, it was determined that these results were the same when the Type I error is different. According to these results, it will be appropriate to prefer interval estimations obtained with sample variance estimator based on Trimmed Mean since it provides narrower confidence interval for the difference of the variances of two nonnormal populations.

This research consists of a cross-sectional survey studying the local knowledge about arid-semi arid truffles, their use and their ethnomycological aspects, in the hope of discussing the importance of truffles in socioeconomic life, for the local ecology and in folk traditions. 230 truffle gatherers from Eastern Turkey were interviewed. Truffles usually appear from early March to late April (68.3%), seen at barren areas that are not plowed (95.2%), and grow in sandy soils (97.8%). Truffle gatherers look for truffle types at areas where the soil bulges and cracks (97.0%), or where kumi plant grows (95.2%), and they find these using their personal experience (94.8%). Observed species included red, reddish brown, brown (100%), yellowish white (60.4%), and rarely black (30.0%) morphological types. The locals have expressed that they collect about 2 kg or less truffles per day (68.7%), and the financial profit is high (68.3%). They acquired information from their families and elders (92.6%) about mushrooms, and they gather truffles for nutrition (97.8%), for their high nutritious value (67.8%), as they are a natural food source (94.3%), and because of the feeling of satiety they provide (95.7%). Rain (97.8%), soil type (62.2%) and also host plant (Helianthemum spp.) affect the growth of the mushroom. Truffles are usually fried with eggs when cooking (84.8%), preserved in refrigerators (93.0%), and the quality of edibility is high (83.9%). T. boudieri is preferred for commercial use, whereas other types (P. lefebvrei, T. olbiensis and P. juniperi) are mostly used for daily consumption because they do not provide financial profit.

Rasgele deneylerde deney ve kontrol gruplarının ortalamaları arasındaki farkın yanısıra varyanslar arasındaki farkın incelenmesi de analiz sonuçlarını yorumlamada faydalı olabilir. Normal dağılımlı yığınların varyansının tahmininde yansız örnek varyansı tahmin edicisi kullanılır. Normal dağılımlı olmayan yığınların varyansının tahmininde ise örnek varyansı tahmin edicisinin sağlam istatistik özelliği göstermediği ve bu tahmin edici ile elde edilen güven aralıklarının kapsama olasılıklarının nominal güven düzeyinden oldukça düşük olduğu bilinir. Böyle durumlarda yığın varyansının tahmini için sağlam tahmin edicilerin kullanılması gerekir. Bu çalışmada normal dağılımlı olmayan iki yığının varyanslarının farkının tahmini için sağlam tahmin edicilere dayalı güven aralığı yöntemleri önerilmiştir. Bu güven aralıkları aynı simülasyon koşulları altında kapsama olasılığı ve ortalama aralık genişliği bakımından karşılaştırılmıştır. Bu tahmin ediciler Winsorized ve Budanmış varyans, ikili uzaklıklara, ikili uzaklıkların medyanına ve medyandan mutlak sapmaların medyanına dayalı olarak elde edilen örnek varyansı tahmin edicileridir. Yapılan simülasyon çalışmasında ilk olarak bu tahmin edicilerin dağılım biçimleri belirlenmeye çalışılmıştır. Daha sonra normal dağılımlı olmayan iki yığının varyanslarının farkı için bu tahmin edicilere dayalı güven aralıkları, kapsama olasılıkları ve ortalama aralık genişlikleri bakımından karşılaştırılmıştır. Simülasyon çalışmasına göre bu tahmin ediciler ile elde edilen güven aralıklarının kapsama olasılıklarının tüm durumlarda nominal güven düzeyine çok yakın oldukları belirlenmiştir. Buna karşın nominal güven düzeyleri aynı iken, Budanmış Ortalamaya dayalı örnek varyansı tahmin edicisi (trimmed varyans) ile elde edilen ortalama aralık genişliklerinin diğer tahmin ediciler ile elde edilen ortalama aralık genişliklerine göre daha dar olduğu görülmüştür. En geniş ortalama aralık genişliklerinin ise medyandan mutlak sapmaların medyanına dayalı örnek varyansı tahmin edicisi ile elde edildiği belirlenmiştir. Ayrıca I. Tip hata farklı olsa da bu sonuçların aynı olduğu saptanmıştır. In random experiments, most analyses are based on interpretation of the difference between the means of experiment and control groups. Therefore, studying the difference between the variances of the experiment and control groups may also be useful in interpreting the analysis results. In estimation of variances of normal populations, sample variance estimator is used. It is known that sample variance estimator does not display robust statistics features in the estimation of nonnormal population variance and the coverage probabilities of the confidence intervals obtained with this estimator have much lower values compared to the nominal confidence interval. In such cases, it is necessary to use robust estimators for estimation of population variance. In this study, it was proposed that confidence interval methods based on robust estimators were used to estimate the difference of variances of two nonnormal populations. This confidence intervals were compared in terms of coverage probabilities and average length widths under same simulation conditions. These estimators are Winsorized and Trimmed variances. In addition, they are sample variance estimators based on binary distances, median of binary distances and median of the absolute deviations from the median. Firstly, the distributions of estimators were determined with the simulation study. Therefore, confidence intervals based on this estimators for the difference of the variances of two nonnormally populations were compared in terms of coverage probabilities and average interval widths. According to simulation study, it was determined that the coverage probabilities of confidence intervals based on the estimators were very close to the nominal confidence level in any case. However, it was seen that the average interval widths of confidence intervals obtained with sample variance estimator based on Trimmed Mean were narrower compared to the average interval widths of confidence intervals obtained with other sample variance estimators. The largest average interval widths were obtained with estimator based on median of the absolute deviations from the median. In addition, it was determined that these results were the same when the Type I error was different. 123

This study aimed to determine the knowledge, attitude and behavior level of the academic staff at Bitlis Eren University BEU related to GMOs. The general information levels GILs were found not to be significant p > 0.05 , in terms of gender, age, department, education level and title, but found to be significant p < 0.05 in terms of marital status. The GILs were changing between 19 and 36 and were 28.1±3.1 on average. According to these data, it can be said that academic staff have a medium of knowledge about GMOs. They have stated that GMOs are commonly used in agriculture fields 91.7% ; they are mostly informed via TV/radio or the internet 34.0% ; the most reliable resources are universities 69.9% ; they want to be mostly informed about its benefits, risks 75.0% and its place in Turkey 51.3% ; they think they consumed GMOs 75.6% , they are not informed about labels 76.9% , they do not have enough information 60.9% and that they want to be informed 92.9% about the topic. The academic staff said that the effects of GMOs are too dangerous, they do not find the applications ethique, they wouldn’t consume GMOs and they were absolutely against to the import of GMOs. In conclusion, it has been revealed that more information is necessary about GMOs as they will be very important for the new generations., B u çalışmada; Bitlis Eren Üniversitesi BEÜ akademik personellerinin GDO konusunda bilgi tutum ve davranışlarının belirlenmesi amaçlanmıştır. Genel bilgi seviyeleri, cinsiyet, yaş, bölüm, eğitim düzeyi ve ünvan açısından anlamlı bulunmamış p > 0.05 ; fakat medeni durum açısından anlamlı p < 0.05 bulunmuştur. Genel bilgi seviyeleri 19 ve 36 puan arasında değişmekte olup, ortalama 28.1±3.1’dir. Bu verilere göre; akademik personellerin GDO konusunda orta düzeyde bir bilgiye sahip olduğu söylenebilir. GDO’ların daha çok tarım alanında kullanıldığını % 91.7 , radyo/TV, internet yoluyla bilgilendiklerini % 34.0 , en güvenilir kaynağın üniversiteler olduğunu % 69.9 , daha çok faydaları ve riskleri % 75.0 ile Türkiye’deki durumu % 51.3 hakkında bilgilenmek istediklerini ve ayrıca; bu ürünleri tükettiklerini düşündüklerini % 75.6 , etiketlemeler % 76.9 ile konu hakkında % 60.9 bilgi sahibi olmadıklarını ve bilgilenmek istediklerini % 92.9 ifade etmişlerdir. GDO’nun etkilerinin çok tehlikeli olduğunu, genetik uygulamaları etik bulmadıklarını, tüketmeyeceklerini ve ithaline kesinlikle karşı olduklarını belirtmişlerdir. Sonuç olarak; GDO yeni nesiller için oldukça önem arz edeceğinden daha fazla bilgiye gereksinim olduğu ortaya çıkmıştır