ÖRNEKLEME YÖNTEMLERİ VE UYGUN ÖRNEKLEM BÜYÜKLÜĞÜNÜN BELİRLENMESİ: ÖZLÜ BİR BAKIŞ

Abstract

Örneklem büyüklüğünün belirlenmesi çoğu uygulamalı araştırma için tartışmalı bir konu olmuştur, öyle ki bir örneklemin ne kadar büyük olması gerektiğinin yanlış belirlenmesi çalışmada hatalı çıkarımlara yol açabilmektedir. Bu nedenle bu çalışmada özellikle basit tesadüfi örnekleme, sistematik örnekleme, tabakalı örnekleme ve küme örneklemesi olarak özetlenebilecek olasılıklı örnekleme yöntemlerinde ve çeşitli araştırma tasarımlarında gerekli minimum örneklem büyüklüğünün saptanmasına yönelik ölçütlerin ve formülasyonların öne çıkarılması amaçlanmıştır. Ayrıca istatistiksel güç ve etki büyüklüğünün örneklem büyüklüğünün belirlenmesindeki yerine ve Cohen'in (1988) çalışmasına dayanarak regresyon analizi için örneklem büyüklüğü hesaplamalarına da değinilmiştir.

Keywords

• Örneklem büyüklüğü
• Örnekleme tasarımı
• Olasılıklı örnekleme
• Basit tesadüfi örnekleme
• Tabakalı örnekleme
• Küme örneklemesi

SAMPLING METHODS AND APPROPRIATE SAMPLE SIZE DETERMINATION: A CONCISE OVERVIEW

Abstract

Sample size determination has been a controversial issue for many applied researches, such that incorrect determination of how large a sample should be may lead to erroneous inferences in the study. For this reason, in this paper it has been aimed to highlight the general criteria and formulations for detecting the required minimum sample size especially in probability sampling methods -which can be summarized as simple random sampling, systematic sampling, stratified sampling and cluster sampling- and various research designs. Besides, the place of statistical power and effect size on sample size determination and the sample size computations for regression analysis based on the study by Cohen (1988) have also been mentioned.

Keywords

• Sample size
• Sampling design
• Probabilistic sampling
• Simple random sampling
• Stratified sampling
• Cluster sampling

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