MITHA ARVIRA OKTAVIANI, 101011001 (2014) PERBANDINGAN HASIL ANALISIS NORMALITAS DISTRIBUSI METODE KOLMOGOROV-SMIRNOV, LILLIEFORS, SHAPIRO-WILK, DAN SKEWNESS-KURTOSIS (Aplikasi Pada Data Antropometri Posyandu Teratai III RT. 01-02 RW. 09 Pegirian Surabaya Tahun 2014). Skripsi thesis, UNIVERSITAS AIRLANGGA.

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Abstract

There are many kinds of normality test method in determining the data whether has the normal distribution or not. Some of these methods result can make different decision. This different results can be misleading and confusing practitioners in performing statistical tests. Normality test needed a method that can produce consistent decisions. The aim of this research was to compare the results of distribution normality analysis with the Kolmogorov-Smirnov test, Lilliefors test, and Shapiro-Wilk test toward Skewness-Kurtosis test and analyze which one has the best consistency level. This research used secondary data from the report of activity result in posyandu Teratai III Pegirian Surabaya on Mei 2014. The data is about Weight (W), Height (H), and Index W/H. Total population of the posyandu was 80 subject, then doing simulation of the data so that obtained samples with multiples of 10, there are 10, 20, 30, 40, 50, 60, and 70. Samples were selected by simple random sampling method. This research can be performed the results of normality test decision on each samples and each repetition. This research resulted in the percentage consistency level of the results in three method of normality test toward Skewness-kurtosis test result, there are from Kolmogorov-Smirnov test was 68.26%, from Lilliefors test was 82.54%, and from Shapiro-Wilk test was 90.48%. The conclusion is Shapiro-Wilk test has the best consistency level and then followed by Lilliefors test and Kolmogorov-Smirnov test. The next researchers can analyzed the normal distribution suggested using other methods such as the Anderson-Darling test, Cramer-von Mises test, or Fisher's test cumulate.

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