Concept of Normality and Homogeneity Testing

 Concept of Normality and Homogeneity Testing

1.      Normality Testing

Normality  testing  is  a  basic  requirement  that  should  be  fulfilled  in parametric analysis. Before doing a further analysis towards the data, normality of the data should be tested first. It is intended to investigate whether the data is in normal  distribution  or  not.  According  to  Priyatno(2012:33),  normality  testing being important since by a normal distribution of the data, means that data could represent the population. In this case, to test the normality the researcher uses SPSS  16.00  with  One-Sample  Kolmogorov-Smirnov  method.  The  normality testing is done towards  both pre-test and post-test score. The students’ names below  were  identified  based  on  the  initial  name  of  the  students

2.      Homogeneity Testing

Homogeneity testing is intended to know whether the variance of data is homogeneous or not. In this case, the homogeneity will be tested to the sample that  was  used  to  collect  the  data.  The  procedure  used  to  test  the  variance  of homogeneityis  by  determining  Fmaxvalue.  In  homogeneity  test  Fvalue  (empiric) should  be  lower  than  F  table  (theoretic).  In  order  to  get  Fmaxvalue,  the  data  of students’ score on pre-test and post-test


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