Normality and Homogeneity Test Hypothesis Testing

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B. Normality and Homogeneity Test

The normality and homogeneity test must be done before analyzing the data by using inferential analysis. The function of normality test is to know whether the sample is in normal distribution or not, while homogeneity test is to know whether the data are homogeneous or not. The description of each test is as follows: 1. Normality Test The sample is on normal distribution if L o L obtained is lower than L t at the level of significance a = 0.05 or L L t . No Data The number of Sample L obtained L o L Table L t Alfa a Distribution of Population 1 A 1 B 1 11 0.112 0.249 0.05 Normal 2 A 1 B 2 11 0.106 0.249 0.05 Normal 3 A 2 B 1 11 0.203 0.249 0.05 Normal 4 A 2 B 2 11 0.205 0.249 0.05 Normal 5 A 1 22 0.119 0.190 0.05 Normal 6 A 2 22 0.150 0.190 0.05 Normal 7 B 1 22 0.169 0.190 0.05 Normal 8 B 2 22 0.125 0.190 0.05 Normal Table 11. The Normality Test commit to user 2. Homogeneity Test The purpose of homogeneity test is to know that the data are homogenous. If c o 2 is lower than c t at the level of significance a = 0.05 or c o 2 c t , it can be concluded that the data are homogenous. Sample Df 1df s i 2 Log s i 2 df log s i 2 1 2 3 4 10 10 10 10 0.1 0.1 0.1 0.1 25.05 23.02 27.85 17.42 1.399 1.362 1.444 1.241 13.99 13.62 14.44 12.41 40 0.4 54.46 Table 12. The Homogeneity Test c 2 = 2.303{B – SlogS i x n-1} = 2.30354.721 – 54.469 = 0.58 Based on the result of calculation above, it can be concluded that the c o 2 0.58 is lower than c t at the level of significance a 5 = 7.81. Because c 2 c t 0.58 7.81, the data are homogenous.

C. Hypothesis Testing

After knowing that the data are normal and homogeneous, hypothesis testing can be conducted. The data analysis is done by using multifactor analysis of variance 2 x 2. H is rejected if F o F t , it means commit to user that there is a significant difference and an interaction. If H is rejected the analysis is continued to know which group is better using Tukey test. The multifactor analysis of variance 2 x 2 and Tukey test are described below: 1. Summary of a 2 x 2 Multifactor Analysis of Variance Source of Variance SS df MS F F t 0,05 F t 0,01 Between columns 209.45 1 209.45 8.98 4.08 7.31 Between rows 432.82 1 432.82 18.55 4.08 7.31 Columns by rows interaction 1,265.82 1 1,265.82 54.24 4.08 7.31 Between groups 1,908.09 3 636.03 - - - Within groups 933.46 40 23.34 - - - Total 2,841.54 43 - - - - Table 13. Multifactor Analysis of Variance Reading Habits Team-games- tournament A 1 Direct Instruction Method A 2 Sum High B 1 Group 1 Group 2 X = 79.36 X =64.27 X =71.82 Low B 2 Group 3 Group 4 X = 62.36 X =68.73 X =65.55 Total X = 70.86 X =66.5 X =68.68 Table 14. The Mean Score commit to user Based on the table above, it can be concluded that: a Because Fo between columns 8.98 is higher than F t at the level of significance a = 0.05 4.08 and F t at the level of significance a = 0.01 7.31, the difference between columns is significant. Because the mean score of students who are taught using TGT is 70.86 and the mean score of students who are taught using Direct Instruction method is 66.50, it can be concluded that TGT is more effective than Direct Instruction method to teach reading. b Because F between rows 18.55 is higher than F t at the level of significance a = 0.05 4.08 and F t at the level of significance a = 0.01 7.31, the difference between rows is significant. Because the mean score of students having high reading habits is 71.82 and the mean score of students having low reading habits is 65.55, it can be concluded that the students having high-reading habits have higher reading comprehension than students having low-reading habits. c Because F interaction 54.24 is higher than F t at the level of significance a = 0.05 4.08 and F t at the level of significance a = 0.01 7.31, there is an interaction effect between teaching methods and students’ reading habits in teaching reading. Because the mean score of students having high reading habit who are taught by TGT 79.36 is higher than the students having high reading habit who are taught by DI 64.27, it can be concluded that TGT is more effective than DI to teach reading for students having high reading habits. Because the commit to user mean score of the students having low reading habit who are taught using DI is 68.73 is higher than the students having low reading habit who are taught using TGT 62.36, it can be concluded that DI is more effective than TGT to teach reading for students having low reading habit. It means that the effect of teaching methods on the students’ reading comprehension depends on the level of students’ reading habit. So, there is an interaction between teaching methods TGT and DI, and reading habits in teaching reading; in which TGT is more effective for students having high reading habit and DI is more effective for students having low reading habit. 2. Summary of Tukey Test The finding of q is found by dividing the difference between the means by the square root of the ratio of the within group variation and the sample size. Between group q o q t 0.05 q t 0.01 Significantly Meaning A 1 – A 2 4.24 2.95 4.02 Significant B 1 B 2 B 1 – B 2 6.09 3.11 4.02 Significant A 1 A 2 A 1 B 1 – A 2 B 1 10.33 3.11 4.39 Significant A 1 B 1 A 2 B 1 A 1 B 2 – A 2 B 2 4.36 3.11 4.39 Significant A 1 B 2 A 2 B 2 Table 15 Summary of Tukey Test a. Because q o between columns A 1 and A 2 4.24 is higher than q t at the level of significance a = 0.05 2.95 and q t at the level of significance a = 0.01 4.02, Team-Games-Tournament method differs significantly from Direct Instruction Method to teach reading. Because commit to user the mean score of A 1 70.86 is higher than A 2 66.5, it can be concluded that TGT is more effective than Direct Instruction Method b. Because q o between row B 1 and B 2 6.09 is higher than q t at the level of significance a = 0.05 2.95 and q t at the level of significance a = 0.01 4.02, the students having high reading habits differ significantly from those having low reading habits in reading. Because the mean score of B 1 71.82 is higher than B 2 65.55, it can be concluded that the students having high reading habits have better reading comprehension than those having low reading habits. c. Because q o between cells A 1 B 1 and A 2 B 1 10.33 is higher than q t at the level of significance a = 0.05 3.11 and q t at the level of significance a = 0.01 4.39, Team-Games-Tournaments differs significantly from Direct Instruction method for the students who have high reading habits. Because the mean score of A 1 B 1 79.36 is higher than A 2 B 1 64.27, it can be concluded that Team-Games-Tournaments is more effective than Direct Instruction Method to teach reading for students having high reading habits. d. Because q o between columns A 1 B 2 and A 2 B 2 4.36 is higher than q t at the level of significance a = 0.05 3.11, Direct Instruction Method differs significantly from Team-Games-Tournament for the students having low reading habits. Because the mean score of A 2 B 2 68.73 is higher than A 1 B 2 62.36, it can be concluded that Direct Instruction commit to user method is more effective than Teams-Games-Tournaments to teach reading for students having low reading habits.

D. Discussion