Student X
Y XY
X
2
Y
2
51 98
75 7350
9604 5625
52 91
75 6825
8281 5625
53 96
85 8160
9216 7225
54 112
75 8400
12544 5625
55 124
65 8060
15376 4225
56 86
75 6450
7396 5625
57 110
75 8250
12100 5625
58 107
75 8025
11449 5625
59 114
70 7980
12996 4900
60 103
75 7725
10609 5625
61 108
75 8100
11664 5625
62 97
85 8245
9409 7225
63 91
80 7280
8281 6400
64 125
65 8125
15625 4225
65 87
85 7395
7569 7225
66 100
75 7500
10000 5625
67 110
75 8250
12100 5625
68 95
85 8075
9025 7225
69 92
75 6900
8464 5625
70 97
75 7275
9409 5625
71 117
75 8775
13689 5625
72 106
75 7950
11236 5625
73 120
65 7800
14400 4225
74 115
75 8625
13225 5625
75 93
85 7905
8649 7225
76 120
70 8400
14400 4900
77 114
75 8550
12996 5625
78 93
75 6975
8649 5625
79 106
75 7950
11236 5625
80 100
75 7500
10000 5625
81 109
75 8175
11881 5625
82 121
60 7260
14641 3600
83 116
75 8700
13456 5625
Student X
Y XY
X
2
Y
2
84 77
87 6699
5929 7569
85 117
75 8775
13689 5625
86 110
85 9350
12100 7225
87 108
75 8100
11664 5625
88 105
75 7875
11025 5625
89 131
60 7860
17161 3600
90 108
75 8100
11664 5625
91 84
80 6720
7056 6400
92 102
75 7650
10404 5625
93 96
88 8448
9216 7744
94 121
70 8470
14641 4900
95 109
75 8175
11881 5625
96 113
75 8475
12769 5625
97 96
80 7680
9216 6400
98 102
75 7650
10404 5625
99 112
75 8400
12544 5625
100 115
75 8625
13225 5625
101 102
85 8670
10404 7225
102 112
75 8400
12544 5625
103 87
86 7482
7569 7396
104 115
75 8625
13225 5625
105 110
75 8250
12100 5625
106 122
65 7930
14884 4225
107 81
88 7128
6561 7744
108 113
88 9944
12769 7744
109 107
75 8025
11449 5625
110 103
80 8240
10609 6400
111 86
80 6880
7396 6400
112 129
65 8385
16641 4225
113 97
82 7954
9409 6724
114 101
75 7575
10201 5625
115 114
75 8550
12996 5625
116 122
70 8540
14884 4900
Student X
Y XY
X
2
Y
2
117 106
75 7950
11236 5625
118 96
75 7200
9216 5625
119 124
70 8680
15376 4900
N=119 ∑X =12605 ∑Y=8969
∑XY=943185 ∑X
2
=1353883 ∑Y
2
=680321
Based on the Table 4.2, the sum of the anxiety variable X is 12605 and the sum of the reading skill variable Y is 8969. The sum of multiply
score of both variables XY is 943185. The sum of quadrate score of anxiety X2 is 1353883 and the last, the sum of quadrate of reading skill Y2 is
680321.
B. Data Analysis and Testing Hypothesis
1. Data Analysis
a. Analysis of Data Linearity
The linearity of students’ anxiety and reading skill data were analyzed using IBM SPSS program and presented by ANOVA Table.
Linearity test was done as one of the requirement of correlational analysis. The result of the analysis is represented in following table:
Table 4.3 ANOVA Table
Sum of Squares
df Mean
Square F
Sig. Reading
Anxiety Between
Groups Combined
3403.124 45
75.625 6.150
.000
Linearity
2515.922 1
2515.922 204.59
2 .000
Deviation from Linearity
887.202 44
20.164 1.640
.030
Within Groups 897.700
73 12.297
Total
4300.824 118
The Table 4.1 reveals the linearity distribution of the both data students’ anxiety and their reading skill. The result of the linearity is in
the significance of 0.00. It showed that the result is lower than the level of significance 0.05 which the score is 3.92 0.00 3.92. Thus, the result
means that the data have linear distribution and parametric statistic is used in this study.
b. Analysis of Data Normality
Normality test was used by the writer at the 0.05 level of significance where the value is 0.124. The normality test was implemented
to see whether the data populations are normally distributed or not.
Table 4.4 Kolmogorov-Smirnov Table
Kolmogorov-Smirnov
a
Statistic df
Sig. Anxiety
.059 119
.200 Reading
.096 119
.200 . This is a lower bound of the true significance.
a. Lilliefors Significance Correction
From the Table 4.2, it can be seen that the Sig. of Anxiety is 0.200 and Sig. of Reading skill is 0.200. If the significance score 0.124, the
data comes from the normal population. However, if the significance score 0.124, the data does not come from the normal population. It can
be concluded that the data are normally distributed because the Sig. of anxiety is higher 0.200 0.124 and the Sig. of reading is also higher
0.200 0.124. In other words, the data result in the data is normally distributed.
c. Analysis of Correlation Product Moment
After getting the classification result of each score above, it was time to calculate the scores to Pearson Product Moment Formula:
r
xy
=
–
In which:
r
xy
=
–
=
–
=
= r
xy
= -0,761221 r
xy
N ∑X
∑Y ∑XY
∑X
2
∑Y
2
= the correlation coefficient score = number of sample
= the sum of total score in variable X = the sum of total score in variable Y
= the sum of multiply score of variable X and Y = the sum of the quadrate score in variable X
= the sum of the quadrate score in variable Y
To make sure the result of the calculation above, the writer used SPSS program. The using of SPSS is to know whether the calculation that
the writer did manually was correct and to make sure that there is no mismatching calculation between scores that the researcher counted. The
result of SPSS was described such as follow:
Table 4.5 Pearson Product Moment Table
Reading Anxiety
Reading Pearson Correlation 1
-.761 Sig. 2-tailed
.000 N
119 119
Anxiety Pearson Correlation -.761
1 Sig. 2-tailed
.000 N
119 119
. Correlation is significant at the 0.01 level 2-tailed.
The results of those two calculations manual calculation and SPSS calculation are same, in which show the value of r
xy or
r
o
= -0.761. It means that there is no mismatch in the process of calculating the data by
doing manually or using SPSS program. d.
Analysis of Determinant Coefficient In addition, to know the percentage contribution of X variable to Y
variable, it can be found from coefficient of determination through this formula:
R = r
2
x 100
In which: R
= value of determinant coefficient r
2
= value of the squared correlation coefficient
R = -0.761
2
x 100 = 0.579 x 100
