The Data Analysis

2. The Data Analysis

a. The Students’ Writing Skill

To determine the students’ ability in writing skill, the researcher uses Fill in Exercise as the test. The researcher formulates the students’ score for each number of

the items by using formula from Purwanto (2009:89), as follows: True answer = 1

False answer = 0 The researcher counts the students’ value by using the formula from Djiwandono (2008:46) as follows:

After getting the percentage of the students’ value, the researcher uses the descriptors for writing suggested by Carrol and West (1989) in Flowerdew and Miller (2005:208) as follows: 0%

= Nonscorable 10% - 30% = Limited

40% - 50% = Adequate 60%- 70% = Good 80% - 90% = Very good

100% = Excellent

1) Mean Score and Standard Deviation

According to Brown (1996:102), mean is probably the single most important indicator of central tendency. Establishing the mean in the research is important since it takes into account the individual weighting of every score. To find out the mean score, the researcher uses the formula from Djiwandono (2008: 212), as follows:

It Means:

X = The mean for the data ΣX

= The sum of all of scores N

= Number of sample Establishing the Standard Deviation is used to measure the variability of the

distribution of the test scores. To get the standard deviation, the researcher uses the formula from Djiwandono (2008: 215) as follows:

Note: S

= The standard deviation

X = The score of item

̅ = The mean of the data N

= The number of the sample

2) Variance

Variant is the quadrate from standard deviation. To determine the variant, the researcher uses the formula suggested by Djiwandono (2008: 217):

It Means: S 2 = Variance

X = The score of item ̅

= The mean for the data N

= The number of the sample

b. Mean Score

Mean score function to compare between the amount of the data and the number of the data. In getting the mean score, the researcher also uses the formula from Djiwandono (2008: 212) as follows:

Where:

X = The sum ∑X = The Total Score

N = Sample

c. Standard Deviation

Standard deviation is function to find out the average of the range of each data will mean. According to Arikunto (2001: 263), standard deviation is showing the students’ position in order to separate the class into group. Ary, Jacobs, and Razavieh (2002: 134) define standard deviation as:

Where: σ

: Standard Deviation ∑X

: Sum of the squares of each score (each score is first squared, then these squares are summed)

( ) : Sum of the scores squared (the scores first summed, then this total is squared)

N : Number of cases.

d. Normality of Data

The normality of the data is used to know the normal data distribution of experimental group and control group. The sample is normal distribution, so the The normality of the data is used to know the normal data distribution of experimental group and control group. The sample is normal distribution, so the

1) Calculate the standard value (z) with this formula: ̅

2) Determine the broad under the standard of normal curve from 0 to z in the table and determine F(z) by following these rules below:

a) For the z signed negative

F(z) = 0.5 – the broad under the standard of normal curve from 0 to z

b) For the z signed positive

F(z) = 0.5 + the broad under the standard of normal curve from 0 to z

3) Determine S(z) with this formula: ()

4) Determine the absolute value from F(z) – S(z)

5) Determine the highest absolute from F( ) S( ) as Lo

6) Determine by following the criticl value table to Liliefors test = ()

7) Drawing a conclusion by following these rules below:

a) If Lo <

, the sample has the normal distribution

b) If Lo > , the sample doesn’t has the normal distribution

Table 4

THE WORK TABLE for LILIEFORS FORMULA

x- ̅

F( ) S( ) |F(Zi – S(Zi)|

Conclusion

e. Homogeneity of Data

The homogeneity is used to figure out the homogeneity of the data of the sample and the population. Huck (2012:227) provides the formula to determine the homogeneity if the number of sample of two groups is the same. It is Harley Test Formula as follows:

With: Variance = the square of standard deviation (S 2 )

dk

= n 1 -1 , n 2 -1

homogen = F table >F count

f. Hypotheses of the Research

In the research, the results from both of the classes (experimental class and control class), are used by the researcher to examine the hypothesis. So, the research hypotheses in the research are:

Ha : There is a significant effect of Word Chain Game on the students’ ability in writing words at the eighth grade of SMP Negeri 1 Hiliserangkai in 2015/2016.

Ho : There is no a significant effect of Word Chain Game on the students’ ability in writing words at the eighth grade of SMP Negeri 1 Hiliserangkai in 2015/2016.

The result of post-test has a normal distribution and homogenous, so the researcher examines the hypothesis by using parametric statistic (t test) as its formula written by from Sugiyono (2008: 273), as follows:

Which: t = t count

1 = the mean of experimental group

2 = the mean of control group n = total of sample

1 = variants of experimental group

2 = variants of control group Then it is confirmed to distribution where the level of significance

0.05 and statistic t count above is student distribution dk = n 1 +n 2 -2.

Examining criteria is Ho is accepted if – t (1- 1/2 α) < t < t (1- 1/2 α) and the others t, H o is unaccepted.