This course is designed in such a way that after attending it the students will be able to: (1) calculate and apply measures of location and measures of dispersion; (2) perform test of hypothesis as well as calculate confidence interval for a population parameter for single sample and two sample cases; (3) compare group means by using t-test and ANOVA; (4) learn non-parametric test such as the Chi-Square test for Independence; and (5) compute and interpret the results of Correlation Analysis, Bivariate and Multivariate Regression for forecasting. In relation to these expected outcomes, this course provides students with the basic concepts and application of quantitative data analysis and statistical computing on research, assessment and evaluation of English language education. To provide students with pragmatic tools for assessing statistical claims and conducting their own statistical analyses, topics covered include measurement scales, basic descriptive measures, measures of correlation, probability theory, confidence intervals, inferential statistics or hypothesis testing, and regression. The classroom activities include lecturing, followed by discussion and practices on the use of statistics in English language education. Outside classroom activities include individual tasks in examining and analyzing the use of statistics in journal articles and a small project on analyzing quantitative data. The assessment of students’ learning is based on  students’ classroom participation, individual assignments, and a quantitative data analysis project.