The main purpose of this course is to help students obtain knowledge and use of theories of estimation and hypothesis testing procedures, together with some of their more important applications. Focus will be put on deriving estimators, compare and evaluate methods like moment methods and maximum likelihood estimators, hypothesis tests and confidence intervals based on interpretation of statistical properties. Topics on Chi-Square, power of a hypothesis test, Neyman-Pearson theory and likelihood ratio tests, ANOVA and hypothesis testing for linear models will also be covered. Students will be prepared with basic statistical inference methods, practice under computational framework using software and apply them to real-world problems.