ECON206 STATISTICS FOR ECONOMISTS II
| Course Code: | 3110206 |
| METU Credit (Theoretical-Laboratory hours/week): | 3 (3.00 - 0.00) |
| ECTS Credit: | 6.0 |
| Department: | Economics |
| Language of Instruction: | English |
| Level of Study: | Undergraduate |
| Course Coordinator: | Prof.Dr. ERKAN ERDİL |
| Offered Semester: | Fall and Spring Semesters. |
Course Objectives
At the end of this course, the student will learn:
- Sampling Distributions and the Central Limit Theorem
- Properties of Point Estimators and Methods of Estimation
- Hypothesis Testing
- Interval Estimation
- Regression and Ordinary Least Squares
Course Content
This course deals with principles of point estimation, properties of point estimators, techniques of estimation, optimality criteria in estimation, interval estimation, hypothesis testing, comparison tests for independent and paired samples, multiple comparisons, non parametric methods, regression, correlation, and analysis of variance and elementary time series analysis.
Course Learning Outcomes
Student, who passed the course satisfactorily will be able to:
- Use sampling distributions
- Analyze propoerties of point estimators
- Estimate confidence intervals
- Test statistical hypothesis
- Use simple linear regression
Program Outcomes Matrix
| Level of Contribution | |||||
| # | Program Outcomes | 0 | 1 | 2 | 3 |
| 1 | The aim of our program is to equip our students with the necessary skills and tools to have a firm understanding of economic theory and policymaking. Our graduates will be able to conceptualize economic problems, assess, analyze, and propose scientific solutions to them. | ✔ | |||
| 2 | Our students are expected to have interdisciplinary perspective to be able to follow and understand daily economic and political developments. | ✔ | |||
| 3 | Our program also trains students to be open to new ideas, be sensitive about social problems surrounding them and work towards providing solutions for these to share with their community. | ✔ | |||
0: No Contribution 1: Little Contribution 2: Partial Contribution 3: Full Contribution