Pre-test Post-test Technique of Data Collection

a. Normality Test

Calculating the normality is important to know whether or not the data has been normally distributed. SPSS software version 22 was used by the writer to calculate the normality of the data. There are two kinds of testing the normality in SPSS; Kolmogrov Smirnov and Shapiro Wilk. The test was established by looking at certain criterion as follows: “If respondents ≥ 50, the Kolmogrov Smirnov normality test is used.” “If respondents ≤ 50, the Shapiro Wilk normality test is used.” The respondents of this study were 41 students in each class, therefore the Shapiro Wilk test was used to calculate the normality of the data. The result of normality can be seen by comparing the significant score to α 0,05. The criterion of hypothesis: : Significant Score 0.05 : Significant Score 0.05

b. Homogeneity Test

As the normality of the data had been obtained, the writer continued the analysis to the next step; which was testing the homogeneity of the data. The homogeneity test was used to see whether the data in both classes were homogeneous or heterogeneous. Based on Levene Statistical in SPSS, the significant score that can be categorized as homogeneous should be higher than 0.05.

3. Statistical Analysis

To see the effectiveness of SQ3R method on students‟ reading comprehension, the statistical analysis with t-test formula was used to determine the final calculation; it was to measure the significance of post- test mean scores in experimental and control class. The t-test formula which used in this calculation is described as follows: 16 = The procedures of t-test are as follows: 17 a. Determining mean of variable X Experimental Class, with formula: = b. Determining mean of variable Y Control Class, with formula: = c. Determining standard of deviation of variable X, with formula: √ d. Determining standard of deviation of variable Y, with formula: √ e. Determining standard error of mean variable X, with formula: √ f. Determining standard error of mean variable Y, with formula: √ 16 Anas Sudijono, Pengantar Statistik Pendidikan, Jakarta: PT. Raja Grafindo Persada, 2008, p. 297. 17 Ibid., 298-299