This course marks the transition of descriptive statistics and probability concepts to inferential statistics, with high priority on regression analysis. It aims to provide students with a solid training in the principles and procedures of statistical theories, which are important for making business decisions. The objectives are therefore to give students statistical knowledge and techniques to analyze and solve real world business problems and to introduce to students computer software techniques for achieving the above objectives. Topics include: sampling theory, confidence interval estimation, hypothesis testing, inferences based on two samples, analysis of variance, Chi-Square test, linear regression and correlation, statistical process and quality control, software packages for statistical analysis.

By the end of the course of study, student will be able to: 1. Demonstrate knowledge of properties of well-known statistical distributions and the concepts of statistical inference; 2. Understand the foundations for classical inference involving confidence intervals and hypothesis testing; 3. Describe the properties of good estimator and use it in point and interval estimations; 4. Use hypothesis testing as a tool for statistical decision making in a business context; 5. Demonstrate an appreciation of one-way and two-way analysis of variance.