| Course Title | Code | Semester | L+U Hour | Credits | ECTS |
|---|---|---|---|---|---|
| Statistics II | ISL208 | 3 + 0 | 3.0 | 4.0 |
| Prerequisites | None |
| Language of Instruction | Turkish |
| Course Level | Graduate |
| Course Type | |
| Mode of delivery | FACE TO FACE |
| Course Coordinator | |
| Instructors | |
| Assistants | |
| Goals | Statistics aims at thinking numerically and helping to interpret and understand the lies behind the numbers. The aim of the course is to provide students with the ability to select and use appropriate data analysis methods in cases where statistical methods are needed and where necessary, in order to teach basic statistical concepts and descriptive, questioning data analysis, sampling and preliminary test, regression and variance analysis. |
| Course Content | The content of this course is point estimation, interval estimation, hypothesis testing, correlation and simple regression, nonparametric tests, chi-square applications, time series analysis. |
| Learning Outcomes |
- 1) To define basic data structures and to reveal their differences without obtaining necessary information in decision problems. 2) Summarize and classify statistical data. 3) Apply statistical approach in information production process. 4) To define the basic concepts of statistics science. 5) To put decision problem or theory related to social sciences statistically. 6) Establish relationships between variables |
| Week | Topics | Learning Methods |
|---|---|---|
| 1. Week | Point and Range Estimation, Properties of Estimators | |
| 2. Week | Hypothesis Tests - Confidence Intervals (For n> 30 or population variance known for large samples, for μ, for μ1 - μ2) | |
| 3. Week | Hypothesis Tests - Confidence Intervals (For n> 30 or population variance for large samples, for p, for p1 - p2) | |
| 4. Week | Hypothesis Tests - Confidence Intervals (for n ≤ 30 in Small Samples or μ1 - μ2 for μ if the population variance is unknown) | |
| 5. Week | Hypothesis Tests - Confidence Intervals (for n ≤ 30 in Small Instances or σ1 / σ2 for σ2 if the population variance is unknown) | |
| 6. Week | Test Power / II. Calculation of Type Error | |
| 7. Week | An overview | |
| 8. Week | MİDTERM | |
| 9. Week | Simple Linear Regression Analysis, EKK Method | |
| 10. Week | Test of Significance of Coefficients, Test of Model's Significance (Variance Analysis) | |
| 11. Week | Estimation of r and R2 | |
| 12. Week | correlation | |
| 13. Week | One Way Analysis of Variance | |
| 14. Week | An overview |
| Ümit Şenesen (2002). Statistics for Business and Economics |
| Program Requirements | Contribution Level | DK1 | Measurement Method |
|---|
| 0 | 1 | 2 | 3 | 4 | 5 | |
|---|---|---|---|---|---|---|
| Course's Level of contribution | None | Very Low | Low | Fair | High | Very High |
| Method of assessment/evaluation | Written exam | Oral Exams | Assignment/Project | Laboratory work | Presentation/Seminar |
| Event | Quantity | Duration (Hour) | Total Workload (Hour) |
|---|---|---|---|
| Midterm 1 | 1 | 2 | 2 |
| Homework 1 | 10 | 2 | 20 |
| Homework 2 | 10 | 2 | 20 |
| Final | 1 | 2 | 2 |
| Practice End-Of-Term | 14 | 2 | 28 |
| Classroom Activities | 14 | 3 | 42 |
| Total Workload | 114 | ||
| ECTS Credit of the Course | 4.0 | ||
