| Course Unit Code | Course Unit Title | Type of Course Unit | Year of Study | Semester | Number of ECTS Credits | | FMA670 | REGRESSION ANALYSIS | Compulsory | 1 | 1 | 6 |
|
| Level of Course Unit |
| Second Cycle |
| Objectives of the Course |
| This course aims to teach estimation methods for theorems and events. In addition; this course provides to better understand some topics in statistics such as measuring relation between variables as quantitatively, estimating parameters of models, testing of hypothesis and forecasting. An elementary knowledge of probability, statistics and matrix algebra is helpful to better understand this lecture. Thus, this course helps to students understanding of theory and application. |
| Name of Lecturer(s) |
| Yrd. Doç.Dr. Mehmet KORKMAZ |
| Learning Outcomes |
| 1 | Analyzing the characteristics of models | | 2 | Learning how to estimate models | | 3 | Learning how to interpret the results obtained from models | | 4 | Improving decision-making skill to apply hypothesis testing for regression parameters | | 5 | Testing the assumptions of OLS method and obtaining the best OLS estimators | | 6 | Understanding variables and relationships among them |
|
| Mode of Delivery |
| Formal Education |
| Prerequisites and co-requisities |
| None |
| Recommended Optional Programme Components |
| None |
| Course Contents |
| Simple and multiple regression |
| Weekly Detailed Course Contents |
|
| 1 | Explaining of basic terms | | | | 2 | Explaining of population and sample regression function | | | | 3 | Estimation of simple linear regression model with OLS method | | | | 4 | Estimation of simple linear regression model | | | | 5 | Properties of OLS estimators, Goodness of Fit and Hypothesis testing | | | | 6 | Properties of OLS estimators, Goodness of Fit and Hypothesis testing | | | | 7 | Expected values and variances of the OLS estimators | | | | 8 | Midterm exam | | | | 9 | Multiple regression analysis: Mechanics and interpretation of the OLS | | | | 10 | Multiple regression analysis: The expected value of the OLS estimators, the variance of OLS estimators, the Gauss-Markov theorem | | | | 11 | Multiple regression analysis: Sampling distributions of the OLS estimators, testing hypotheses about a single population parameters | | | | 12 | Multiple regression analysis: Confidence intervals, testing hypotheses about a single linear combination of the parameters, testing multiple linear restrictions | | | | 13 | Multiple regression analysis: Effects of data scaling on OLS statistics, More on functional forms, selection of regressors, prediction and residual analysis | | | | 14 | Applications | | | | 15 | Applications | | | | 16 | Final exam | | |
|
| Recommended or Required Reading |
|
| Planned Learning Activities and Teaching Methods |
|
| Assessment Methods and Criteria | |
| SUM | 0 | |
| SUM | 0 | | Yarıyıl (Yıl) İçi Etkinlikleri | 40 | | Yarıyıl (Yıl) Sonu Etkinlikleri | 60 | | SUM | 100 |
| | Language of Instruction | | Turkish | | Work Placement(s) | | None |
|
| Workload Calculation |
|
| Midterm Examination | 1 | 3 | 3 |
| Final Examination | 1 | 2 | 2 |
| Quiz | 6 | 10 | 60 |
| Attending Lectures | 14 | 1 | 14 |
| Self Study | 14 | 2 | 28 |
| Individual Study for Homework Problems | 5 | 10 | 50 |
| Individual Study for Mid term Examination | 1 | 10 | 10 |
| Individual Study for Final Examination | 1 | 10 | 10 |
|
| Contribution of Learning Outcomes to Programme Outcomes |
| LO1 | 4 | 4 | 4 | 4 | 4 | 4 | 4 | | LO2 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | | LO3 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | | LO4 | 3 | 3 | 3 | 3 | 3 | 3 | 3 | | LO5 | 4 | 4 | 4 | 4 | 4 | 4 | 4 | | LO6 | 4 | 4 | 4 | 4 | 4 | 4 | 4 |
|
| * Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High |
|
|
|
|
Ordu University Rectorate Building ,Cumhuriyet Campus , Center / ORDU / TURKEY • Tel: +90 452 226 52 00
|