To provide an additional vivid description of the data distribution of Extensive Reading achievement, the histogram of frequency distribution is
presented in figure 4.1 as follows:
Figure 4.2 The Histogram of Data of Extensive Reading Achievement
From the figure 4.2 above, the total number of students is 45 students. The students who got score 14, 70, 71, 72, 73 and 75 are one student for each,
students who got score 76 score are 3 students, score 77 are 2 students, score 80 are 3 students, score 81 are 5 students, score 83 are 1 students, score 84 are 5
students, score 85 are 11 students, score 86 are 2 students, score 87 are 3 students, score 88 are 2 students and score 89 and 90 are one students for each. Apparently,
Achievement of Extensive Reading
Achievement of Extensive Reading
from the symmetrical bell-shaped curve, it shows that the data of IQ is normally distributed.
Furthermore, the statistics score of Extensive Reading achievement were counted using Frequencies of Descriptive Statistics in SPSS program in the 24.0
version. The purpose of counting the statistics score is to know the mean, median, mode, maximum and minimum score, and sum. The data is described as follows:
Table 4.5 The Statistics Score of Extensive Reading Achievement
Statistics
Extensive Reading Achievement N
Valid 45
Missing Mean
80.62 Median
84.00 Mode
85 Std. Deviation
11.302 Variance
127.740 Range
76 Minimum
14 Maximum
90 Sum
3628 From the descriptive statistics above, the respondents of this study are 45
students. The mean of Extensive Reading score is 80.62, which means that it is the average score obtained by the students. The median score of the Extensive
Reading is 84.00. Then, the mode of score is 85, which means that most students obtained 85 in Extensive Reading achievement test. Then, the lowest score of
writing is 14 while the highest is 90. Therefore, the range score between the highest and the lowest score is 76. In addition, the standard deviation of Extensive
Reading score is 11.302 with variance 27.740.
In Department of English Education, the score is characterized as follows:
3
80 – 100 = A
70 – 79 = B
60 – 69 = C
50 – 59 = D
– 50 = E An “A” is characterized as an excellent score. It is the highest score and the
students who obtained it, passed the test excellently. Then, “B” is characterized as
a good score. Ne xt, “C” is characterized as a medium score, or the test takers
passed but it is recommended to retake the test or have a remedial test. The last, “D” and “E” are characterized as a bad score or means that the test takers failed to
pass the test.
B. Data Analysis
1. Analysis of the Linearity of Tests
The writer analyzed the linearity of the tests by using SPSS version 24.0. The linearity of the tests was checked in order to see whether the regression of
relationship between two variables in linear. The result of analyzing the linearity of the tests is presented in ANOVA table as follows:
Table 4.6 The Linearity Test Result of the Data
3
Pedoman Akademik Universitas Islam Negeri UIN Syarif Hidayatullah Jakarta 20122013, Jakarta: Biro Akademik dan Kemahasiswaan UIN Jakarta, 2012, p.39.
ANOVA Table
Sum of Squares
Df Mean
Square F
Sig. Reading
Achieve ment
IQ Between
Groups Combined
1194.108 10
119.411 .917
.529 Linearity
5.201 1
5.201 .040
.843 Deviation
from Linearity
1188.907
9
132.101
1.01 5
.448
From the table above, the significance value of deviation from linearity was 0.448, in which the data distribution was good linear because the significance
of deviation from linearity was bigger than 0.05 0.448 0.05. In addition, based on the F
count
= 1.015, and F.005 which counted using the formula in Microsoft Excel as follow:
F
table
= F.INV.RTprobability,deg_freedom1,deg_freedom2 with the the df number in the table above showed that df 9.34, in which found that
F
table
= 2.17. Because F
count
F
table
1.015 2.17, in which the data was significant regression. Overall, the data revealed the Intelligence Quotient IQ
and Extensive Reading achievement have linear regression.
2. Analysis of the Correlation Coefficient
After analyzing the linearity of the data, to measure the correlation coefficient, Pearson Moment Formula was used. The formula was used because
the data distribution is linear. Before doing the calculation, the data is described as below:
Table 4.7 The Data Analysis of IQ X and Extensive Reading Achievement Y
Participants X
Y XY
X2 Y2
Student 1 116
83 9628
13456 6889
Student 2 81
76 6156
6561 5776
Student 3 109
81 8829
11881 6561
Student 4 113
84 9492
12769 7056
Student 5 113
76 8588
12769 5776
Student 6 100
87 8700
10000 7569
Student 7 113
81 9153
12769 6561
Student 8 116
14 1624
13456 196
Student 9 109
81 8829
11881 6561
Within Groups 4426.470
34
130.190 Total
5620.578 44
Participants Y
X XY
Y2 X2
Student 10 131
76 9956
17161 5776
Student 11 119
85 10115
14161 7225
Student 12 121
80 9680
14641 6400
Student 13 109
87 9483
11881 7569
Student 14 116
85 9860
13456 7225
Student 15 109
89 9701
11881 7921
Student 16 113
73 8249
12769 5329
Student 17 121
87 10527
14641 7569
Student 18 113
85 9605
12769 7225
Student 19 113
77 8701
12769 5929
Student 20 121
84 10164
14641 7056
Student 21 106
90 9540
11236 8100
Student 22 113
71 8023
12769 5041
Student 23 113
85 9605
12769 7225
Student 24 121
86 10406
14641 7396
Student 25 116
85 9860
13456 7225
Student 26 133
84 11172
17689 7056
Student 27 109
85 9265
11881 7225
Student 28 91
70 6370
8281 4900
Student 29 131
80 10480
17161 6400
Student 30 116
80 9280
13456 6400
Student 31 116
72 8352
13456 5184
Student 32 116
75 8700
13456 5625
Student 33 121
88 10648
14641 7744
Student 34 116
81 9396
13456 6561
Student 35 106
81 8586
11236 6561
Student 36 113
85 9605
12769 7225
Student 36 121
84 10164
14641 7056
Student 38 119
85 10115
14161 7225