2 METHOD - ANOVA ANALYSIS [1], [2]

2.2 METHOD - ANOVA Analysis [1], [2]: The one-way analysis of variance (ANOVA) is used to determine whether there are any significant differences between the means of two or more independent (unrelated) groups (although you tend to only see it used when there are a minimum of three, rather than two groups). According to Murphy and Davidshofer [21], Analysis of Variance (ANOVA) provides statistical estimates of the variability in test scores associated with systematic differences in the ratings assigned and differences in the ratings obtained. In addition, ANOVA scores can be more accurately generalized over time. Furthermore, Hinkle and et.al stated that, the hypothesis in ANOVA is the mean performance in the population is the same for all groups or equality of population means [22]. In this study, ANOVA was used to test for differences in students‘ motivation based on the demographic characteristics of respondents. The subjects were selected randomly within group to carry out the tests. Therefore, the purpose of this analysis is to determine the influence of the demographic variables on overall students‘ motivation of students at IUH, located in Thanh Hoa Province. The outcome of this analysis is useful for the teachers of English subject to identify which demographic groups influences the perceptions of the students on English language subject. Moreover, correlation and ANOVA analyses were also done to measure the significant of demographics towards the overall student‘s motivation perceptions that help all teachers of English subject and the Dean of all Departments understand their students‘ motivation in learning English subject. In other words, students‘ exam results will be better. - Paired T-test Analysis [1], [2], [23], [24]: T-tests were used to compare the mean differences. There are basically three types of t-tests including two-sample t-test, paired-samples t-test, and one-sample t-test in which a pair T- test is used to compare two population means where you have two samples in which observations in one sample can be paired with conservations in other sample. It computes the differences between values of the two variables for each case and tests whether the average differs from 0.Two-sample t-test is used to compare the means of one variable for two groups of cases-, and paired-samples t-test is used to compare the means of two variables for a single group. Paired sample t-test was applied in this research to compute whether there were any significant differences in students‘ overall motivation on dimension variables including intrinsic motivation, extrinsic motivation, expectancy, anxiety, attitudes, personal goal, and motivational strength.