Notes :
: The number of rank order correlation Rho D
: Difference of rank correlation D = R 1- R 2 N
: Number of students 6 1
: Constant number
The writer used the criteria of reliability are as follows:
16
1. Between 0.800 until 1.000 very high 2. Between 0.600 until 0.799 high
3. Between 0.400 until 0.599 medium 4. Between 0.200 until 0.399 low
5. Between 0.000 until 0.199 very low
J. Data Analysis 1. Fulfillment of the Assumptions
The data gained were statistically analyzed by using technique and steps as the following:
a. Normality Test
The normality test is used to measure whether the data in the experimental class and control class are normally distributed or not.
17
In this research, the writer used Liliefors test as explained below.
1. The hypothesis for the normality test are formulated as follows: H
o:
the data have normal distribution
16
Sugiyono, Metode Penelitian Pendidikan, Pendekatan Kuantitatif, Kualitatif dan R D, Bandung: Alfabeta, 2010, p. 184
17
Sudjana, Metode Statistika, Bandung: Tarsito, 2005, p.466
H
a:
the data do not have normal distribution a. The average rates x are calculated by formula:
=
∑
Notes:
X
i:
the score achieve by students n: the total of students
b. Variants S
2
calculated by formula: S =
∑
Notes:
Xi: the score achieve by students n: the total of students.
c. The test of hypothesis is as follows: 1. For x
1,
x
2,
x
3,
. . . ., x
n
assumed as number z
1
, z
2,
z
3
. . . ,z
n
by using the formula:
Zi = 2. For each this absolute number is arranged in the normal distribution, then it
calculated F Z
i
= P Z ≤ Z
i
3. Next calculate the proportion z
1,
z2
,
z
3. . . .
, Zn then can be smaller or just the same as z
i.
The proportion is represented by Sz =
4. Calculate F Z
i
– Z
i
and calculate the absolute number.
5. Calculate the highest numbers and calls the number as t-
observed.
6. The criteria are as follows: H
o
is accepted if L-
observed
is lower than L-
critical
, means that the distribution of the data is normally distributed.
H
o
is rejected if L-
observed
is higher than L-
critical ,
means that the distribution of the data is not normally distributed.
b. Homogeneity Test
Before administering the data in t-test, it is necessary that the data are homogenous or not. The following explanation is to prove homogenity of the test.
18
a. The hypothesis for the homogenity tests are : H
o:
the variance of the data is homogenous. H
a:
the variance of the data is not homogenous. b. The formula is :
F =
F: The homogenous vb: the biggest variant
vk: the smallest variant
c. The testing criteria are: H
o
is accepted if F-
observed
is lower than F-
critical
at certain level of significance. It uses the level of significant 0.05.
18
Ibid, p.250
