Analysis of Variance ANOVA

commit to user 49   N X X x t t 2 1 2 2                N X n X n X n X n X x t b 2 4 2 4 3 2 3 2 2 2 1 2 1 2                 2 2 1 2 b w x x x       N X n X n X x c c c c bc 2 1 2 2 2 1 2 1 2              N X n X n X x r r r r br 2 1 2 2 2 1 2 1 2                 2 2 2 int br bc b x x x x   N X X x t t 2 1 2 2     

E. Technique of Analysing the Data

In techniques of analyzing the data, the researcher used descriptive analysis and inferential analysis. Descriptive analysis is used to know the mean, median, mode, and standard deviation of students’ scores in reading test. Inferential analysis is used to test hypothesis. Before conducting the hypothesis, it is necessary to know the normality and homogeneity. Then, the researcher tested the hyphotesis using Multifactor Analysis of Variance or ANOVA 2X2. It is used to find out the difference between columns and rows. Besides ANOVA, the researcher used Tukey Test to identify the significant difference between groups or cells. To be clearer it is designed as follows:

1. Analysis of Variance ANOVA

The analysis of multi-factors of variance are as follows: a. The total sum of squares: b. The sum of squares between groups: c. The sum of squares within groups: d. The sum between-columns of squares: e. The sum between-rows of squares: f. The sum of squares interaction: commit to user 50   N X X x t t 2 1 2 2      g. df for between - columns sum of squares = C – 1 df for between - rows sum of squares = R – 1 df for interaction C-1 R-1 df for between - groups sum of squares = G – 1 df for within - columns sum of squares =   1 n df for total sum of square = N – 1 C = the number of columns R = the number of rows G = the number of groups n = the number of subject of one groups N = the number of subject of all groups Summary of 2 x 2 ANOVA: Table 3.3 Design for Summarizing ANOVA Teaching Strategy A Intellegence B Semantic Mapping A 1 Lecturing A 2 High B 1 First Group of Students A 1 B 1 Second Group of Setudents A 2 B 1 Low B 2 Third Group of Students A 1 B 2 Fourth Group of Students A 2 B 2 Note: A 1 : the mean score of reading test of experimental class which is taught by using semantic mapping A 2 : the mean score of reading test of control class which is taught by using commit to user 51 lecturing B 1 : the mean score of reading test of students having high intelligence B 2 : the mean score of reading test of students having low intelligence A 1 B 1 : the mean score or reading test of the students having high intelligence who are taught by using semantic mapping A 1 B 2 : the mean score of reading test of the students having low intelligence who are taught by using semantic mapping A 2 B 1 : the mean score or reading test of the students having high intelligence who are taught by using lecturing A 2 B 2 : the mean score of reading test of the students having low intelligence who are taught by using lecturing

2. Tuckey Test