| Course Title | Code | Language | Type | Semester | L+U Hour | Credits | ECTS |
|---|---|---|---|---|---|---|---|
| Statistics II | ISL208 | Turkish | Compulsory | 3 + 0 | 3.0 | 4.0 |
| Prerequisite Courses | |
| Course Level | Graduate |
| Mode of delivery | FACE TO FACE |
| Course Coordinator | |
| Instructor(s) | |
| 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. |
| # | Öğrenme Kazanımı |
| 1 | 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/Applications | Method |
|---|---|---|
| 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 |
| Program Requirements | DK1 |
|---|
| Ders Kitabı veya Notu | Ders Kitabı veya Ders Notu bulunmamaktadır. |
|---|---|
| Diğer Kaynaklar |
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| ECTS credits and course workload | Quantity | Duration (Hour) | Total Workload (Hour) | |
|---|---|---|---|---|
|
Sınavlar |
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 | |||
| *AKTS = (Total Workload) / 25,5 | ECTS Credit of the Course | 4.0 | ||
