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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