3 credits

This course is aimed at providing students with some concepts of statistics necessary for the students to present and analyze the data in educational research. The course includes review of descriptive statistics, probability distributions, hypothesis testing, testing of assumptions (heteroscedasticity, multicollinearity, autocorrelation), correlations for different types of data, regression (simple linear regression, multiple linear regression, logistic regression), MANOVA, one-way ANOVA and two-way ANOVA, some non-parametric tests. To conduct the descriptive and inferential statistics, the students use Excel in the Microsoft Office and the statistical analysis software (SPSS).  Upon the completion of the course, the students are expected to (a) have a solid understanding of statistical concepts, and (b) be able to do some statistical analyses in educational research. 

The program learning outcomes include three aspects: attitudes, knowledge, and skills. The course learning outcomes are (1) the students demonstrate  religious, responsible, and academic attitudes and behaviors that can contribute to the improvement of the quality of communal, national, and state life, (2) the students master relevant and current information and communication technology in English language learning and research, (3) the students possess the ability to make appropriate, professional, and responsible decisions based on analysis of information and data to independently and collaboratively select various alternative solutions to solve learning problems encountered, in accordance with the context, to achieve the best learning outcomes and optimal student development, and (4) the students use relevant and current information and communication technology in English language learning and research. The program learning outcomes can be elaborated into course-specific learning outcomes, as follows: (1) the students are capable of carrying out tasks with a sense of responsibility and demonstrating an attitude of tolerance towards various perspectives and opinions, (2) the students are able to clearly explain testing of assumptions (heteroscedasticity, multicollinearity, autocorrelation), correlations for different types of data, regression (simple linear regression, multiple linear regression, logistic regression), MANOVA, one-way ANOVA and two-way ANOVA, some non-parametric tests, and (3) the students are able to use Microsoft Excel and SPSS to present and analyze the data accurately.