Normal, Beta, Gamma x2 ve Weibull Dağılımlarmın İkili Kombinasyonlarından Alınan Değişik Örnek Genişliğindeki Örneklerin Karşılaştırılmasında Testin Gücü

Bu çalışmada, Normal, Bcita, Gamma i.2 ve Weibull da ğı l ı m ı gösteren populasyonlar ı n, mümkün olan bütün ikili kombinasyonları ndan mcgsle al ı nan örnekler yard ı mı yla hesaplanan F-Testinin gücü ara ştı r ı lm ıştı r. Bunun için, üzerinde durulan populzsyonlar ı n ikili kombinasyonlar ı n ı n ortalamalan aras ı nda 8=0.5, 8=1.0, 8=1.5, 8=2.0, 8=2.5 ve 8=3.0 standart sapmal ı k fark olacak şekilde, dağı l ı mlardan birisindeki gözlemlere, bütün populasyonlarda olduğundan 8; ilave edilmi ştir. Bu populasyonlar ı n ikili kombinasyonlar ı ndan rasgele olarak al ı nan çeşitli örnek genişliği kombinasyonundaki örnekler yard ı mı yla 100 000 simülasyon denemesi sonunda F-Testinin gücü ampirik olarak belirlenmiştir. F-Testinin istenilen güce %80 veya daha yüksek ula şmas ı nda, dağı l ı m şeklinden ziyade, populasyon ortalamalan aras ı ndaki fark ı n büyüklüğüne bağl ı olarak, bu populasyonlardan rasgele al ı nan örneklerdeki deney ünitesi say ı sı n ı n ve bunlar ı n örneklerde eşit veya dengeli olarak bulunup bulunmad ığı n ı n etkili olduğu sonucuna var ı lmışt ı r.

Anahtar Kelimeler:

Testin gücü, Normal da ğı l ım, Beta dağı l ı mı , Gamma Da ğı l ı m ı , Weibull Dağı l ı mı , örnek genişliği

The Power of the Test in the Samples of Various Sample Sizes were Taken from the Binary Combinations of the Normal, Beta, Gamma and Weibull Distributions

In this study, we investigated the power of the ANOVA in the samples taken from the binary combinations of the populations which are showing Normal, Beta, Gamma and Weibull distributions. The differences between the means of the binary combinations of these populations were 8=0.5, 8=1.0, 8=1.5, 8=2.0, 8=2.5 and 8=3.0 standard deviations. For that, one of the populations was added a constant that is 8, The samples which are equal or unequal sample sizes taken randomly from the binary combinations of these populations and calculated power of the F-Test empirically with 100 000 simulated experiment. The result showed that the shape of the distributions ware ineffective on the power of F-Test but effected the sample sizes depend on difference between the means of the populations.

Keywords:

Power of test, Normal distribution, Beta distribution, Gamma distribution, Weibull distribution, sample size,

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