This course is designed for students who are interested in data analysis and modeling in psychology. We will emphasize the basic concepts of probability and statistics. Topics include sample space, conditional probability, Bayes Theorem, the maximum likelihood principle, random variables, expectation and moment, Central Limit Theorem, Law of large numbers, covariance and correlation, ANOVA, and some well-known distributions (such as binomial, multinomial, geometric, Poisson, uniform, exponential, Gaussian, chi-square, t, and F). We will also introduce the concepts of modeling and demonstrate with some examples. Each week there will be a small session on the introduction and practice of the R software to help students understand the aforementioned concepts.