Hypothesis Test Data Analysis Technique

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CHAPTER IV RESULT OF THE STUDY

A. The Data Description

The data analyzed in this research are the result of the test. The scores of students’ reading comprehension and vocabulary mastery can be seen at Appendix 19. The obtained data for each variable reading comprehension and vocabulary mastery are described in Table 3 as follows. Table 3. The Descriptve Statistics of Each Variable Descriptive Statistics N Minimum Maximum Mean Std. Deviation Vocabulary 28 52 80 65.29 7.060 Reading 28 55 85 72.50 6.736 Valid N listwise 28 The whole data are statistically presented at the table above. It is found that the subject of the study is symbolized as N, which consists of 28 students. The highest score of each variable is described in the maximum score and the lowest one is described in the minimum score. The standard deviation describes the dispersion value.

1. Vocabulary Mastery

From the instrument of vocabulary mastery, it is found that the highest score is 80, and the lowest one is 52 in the scoring scale 0-100. The mean and standard deviation are 65.29 and 7.06. Those are interval data, so it can be 50 described with frequency distribution. The frequency distribution is presented at Table 4. Table 4. The Frequency Distribution of the Score of Vocabulary Matery Interval Line of Interval Classes F F cumulative 52 – 56 14.2 4 4 57 – 61 14.3 4 8 62 – 66 28.6 8 16 67 – 71 21.4 6 22 72 – 76 17.8 5 27 77 – 81 3.6 1 28

2. Reading Comprehension

From the instrument of reading comprehension, it is found that the highest score is 85, and the lowest one is 55 in the scoring scale 0-100. The mean and standard deviation are 72.50 and 6.736 respectively. The frequency distribution is presented at Table 5. Table 5. The Frequency Distribution of the Score of Reading Comprehension Interval Line of Interval Classes F F cumulative 55 – 60 3.6 1 1 61 – 65 17.9 5 6 66 – 70 28.6 8 14 71 – 75 28.6 8 22 76 – 80 14.3 4 26 81 – 85 7.1 2 28

B. The Testing of Pre-requirement Analysis

The characteristic of the data of the research determines the techniques of analyzing the data. Before analyzing the data, it is necessary to examine the data. The examination covers normality and linearity. 51

1. Normality Test

The normality test is one of the prerequisite tests before entering the linear regression analysis, that is used to find out whether the data is in normal distribution or not. In this research, the normality test uses the program SPSS 16. The result can be seen from p significance on Lilliefors test; with the interpretation if p value is greater than 0.05 p 0.05, it tells that the distribution of the data is normal, if p 0.05, it tells that the distribution of the data is not normal. The summary of the normality test result of each variable can be seen at Table 6. The computation of SPSS 16 can be seen at Appendix 21. Table 6. The Summary of Normality Test Variable P value Significance Level 5 Decision Vocabulary Mastery Reading Comprehension 0.343 0.119 0.05 0.05 Normal Normal Based on the result of normality test using SPSS 16, it can be concluded that the data are in normal distribution because the significance value of the two variables are greater than 0.05.

2. Linearity Test

Besides normality test, linearity test is also used by the writer for the pre-requirement analysis. Linearity test is aimed to know whether two variables have significance linear regression or not. The testing by utilizing SPSS 16 uses Test for Linearity at the level of significance p = 0.05. Two variables are categorized into linear regression if the p 0.05.