computation of the data See Table 4.3 and Table 4.4 on Appendix. The discussions are detailed as follow:
4.2.1 Mean
The word mean refers to the average score of the students in groups. Christensen 2001:329 defines the means as the arithmetic average of groups of numbers see
also Arikunto 2002. It can be computed by dividing the sum of the scores by number of students in the groups.
Diagram 4.1 RSBI Class Scores
The above diagram shows the English National Examination scores of the RSBI class students. The highest score is 9.80 and the lowest score is 6.60. The score with most
students is 8.60. There are 6 students got 8.60. Bellow is the computation to find the mean of RSBI class.
8.625 24
207 n
Σx
1 1
1
X
= =
=
1
X is the symbol of mean of the first group, in this case is RSBI class.
1
Σx
, the sum from all of the students’ scores is 207 while
n
1
, the number of the students in the first group is 24 see Table 4.3 on Appendix. The result of dividing the sum of
the scores by the number of the students shows the mean of the first group is 8.625.
Diagram 4.2 Regular Class Scores
The above diagram shows the English National Examination scores of the regular class students. The highest score is 9.80 and the lowest score is 6.00. The score with
most students is 8.80. There are 9 students got 8.80. Bellow is the computation to find the mean of regular class.
8.532 44
375.40 n
Σx
2 2
2
X
= =
=
2
X is the symbol of mean of the second group, in this case is regular class.
2
Σx
, the sum from all of the students’ scores is 375.40 while n
2
, the number of the students in the second group is 44 see Table 4.4 on Appendix. The result of dividing
the sum of the scores by the number of the students shows the mean of the second group is 8.532.
From the result above, we know that the mean of RSBI class is higher than regular class.
4.2.2 Variance
In probability theory and statistics, the variance is used as a measure of how far a set of numbers are spread out from each other. It is one of several descriptors of a
probability distribution, describing how far the numbers lie from the mean expected
value. In particular, the variance is one of the moments of a distribution. In that context, it forms part of a systematic approach to distinguishing between probability
distributions. While other such approaches have been developed, those based on moments are advantageous in terms of mathematical and computational simplicity.
The variance is a parameter describing in part either the actual probability distribution of an observed population of numbers, or the theoretical probability
distribution of a not-fully-observed population of numbers. The variance of each group is as follow:
631 .
23 514
. 14
1
1 2
1 1
2 1
= =
− −
Σ =
n X
X S
2 1
S symbolizes the variance of the first group.
2 1
1
X X
− Σ
is the sum quadrate of each first group score minus first group mean. The result of this formula
is 14.514 see Table 4.3 on Appendix. n
1
shows the number of students in the first group. From the calculation above, we get the result of the first group variance is
0.631.
645 .
43 756
. 27
1
2 2
2 2
2 2
= =
− −
Σ =
n X
X S
The
2 2
S symbolizes variance of the second group.
2 2
2
X X
− Σ
is the sum quadrate of each second group score minus second group mean. The result of this
formula is 27.756 see Table 4.4 on Appendix. n
2
shows the number of students in the second group. From the calculation, we get the result of the second group
variance is 0.645. The calculation shows the variance of the first group is 0.631 while the
variance of the second group is 0.645. We can conclude from the calculation that the variance of the regular class is higher than the RSBI class.
4.2.3 Standard Deviation
Kategori