| Ders Adı | Kodu | Yarıyıl | T+U Saat | Kredi | AKTS |
|---|---|---|---|---|---|
| Statıstıcal Applıcatıons Wıth Python | YBS 368 | 6 | 2 + 0 | 2 | 5 |
| Ön Koşul Dersleri | Data structures and Statistics |
| Önerilen Seçmeli Dersler | |
| Dersin Dili | Türkçe |
| Dersin Seviyesi | Lisans |
| Dersin Türü | Seçmeli |
| Dersin Koordinatörü | Prof.Dr. NİHAL SÜTÜTEMİZ |
| Dersi Verenler | |
| Dersin Yardımcıları | Res.Assist. Bahadır AKTAŞ |
| Dersin Kategorisi | Alanına Uygun Öğretim |
| Dersin Amacı | Current applications of the theory by performing a statistical software with Python, students gain the ability to analyze data with appropriate methods. |
| Dersin İçeriği | The content of this course is Python Data Science Ecosystem, data structures, variables, loops, data visualization, probability distributions using Python, parametric and non-parametric two-population comparison analysis, correlation and regression analysis. |
| # | Ders Öğrenme Çıktıları | Öğretim Yöntemleri | Ölçme Yöntemleri |
|---|---|---|---|
| 1 | To be able to know and explain the purpose, scope and importance of statistical science | Lecture, | Testing, |
| 2 | Editing data in Python | Drilland Practice, Lecture, | Homework, |
| 3 | Data visualization in Python | Drilland Practice, Lecture, | Homework, |
| 4 | To be able to comprehend descriptive statistics and make Python applications | Drilland Practice, Lecture, | Testing, Homework, |
| 5 | To be able to comprehend the place of probability concept in statistical science. | Question-Answer, Lecture, | Homework, Testing, |
| 6 | To be able to apply discrete probability distributions in Python | Drilland Practice, Lecture, | Homework, Testing, |
| 7 | To be able to apply continuous probability distributions in Python | Drilland Practice, Lecture, | Homework, Testing, |
| 8 | To be able to apply parametric group comparison analysis in Python | Drilland Practice, Lecture, | Homework, Testing, |
| 9 | To be able to apply non-parametric group comparison analysis in Python | Drilland Practice, Lecture, | Homework, Testing, |
| Hafta | Ders Konuları | Ön Hazırlık |
|---|---|---|
| 1 | Data Structures and Variables | Review of the related chapters of the lecture. |
| 2 | Data Loading, Editing and Function Defining | Review of the related chapters of the lecture. |
| 3 | Loops | Review of the related chapters of the lecture. |
| 4 | Ecosystem of Python Data Science and Basic Concepts of Statistics | Review of the related chapters of the lecture. |
| 5 | Data Visualization | Review of the related chapters of the lecture. |
| 6 | Descriptive Statistics in Python | Review of the related chapters of the lecture. |
| 7 | Probability Distributions | Review of the related chapters of the lecture. |
| 8 | Probability Distributions | Review of the related chapters of the lecture. |
| 9 | Midterm exam | |
| 10 | Parametric Comparison Tests For Two Population | Review of the related chapters of the lecture. |
| 11 | Parametric Variance Analysis | Review of the related chapters of the lecture. |
| 12 | Non-Parametric Comparison Tests For Two Population | Review of the related chapters of the lecture. |
| 13 | Nonparametric Analysis of Variance | Review of the related chapters of the lecture. |
| 14 | Correlation and Regression Analysis | Review of the related chapters of the lecture. |
| Kaynaklar | |
|---|---|
| Ders Notu | |
| Ders Kaynakları | McKinney,W., (2013), Python For Data Analysis, O’Reilly, USA. Başer, M. (2017), Python, Dikeyeksen, İstanbul. |
| Sıra | Program Çıktıları | Katkı Düzeyi | |||||
|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | Can follow new and current technologies and evaluate them | X | |||||
| 2 | Can understand the operation of Corporate Information Systems and use these systems at a basic level | X | |||||
| 3 | Constructs numerical models of basic business problems. | X | |||||
| 4 | Solves modeled business problems with the help of information technologies and interprets the solutions | X | |||||
| 5 | Contributes to informatics oriented projects as a member of the team | X | |||||
| 6 | Effectively uses information technology tools that support teamwork in project management. | X | |||||
| 7 | Master basic business functions and information technologies and establishes the link between them | X | |||||
| 8 | Contributes to the design, development and implementation processes of corporate information systems. | X | |||||
| 9 | Can produce and present quality documentation for all kinds of projects, including entrepreneurship projects. | X | |||||
| 10 | Prepares informative, effective and interesting presentations and presents these presentations. | X | |||||
| Değerlendirme Sistemi | |
|---|---|
| Yarıyıl Çalışmaları | Katkı Oranı |
| 1. Ara Sınav | 50 |
| 1. Ödev | 30 |
| 1. Kısa Sınav | 10 |
| 2. Kısa Sınav | 10 |
| Toplam | 100 |
| 1. Yıl İçinin Başarıya | 50 |
| 1. Final | 50 |
| Toplam | 100 |
| AKTS - İş Yükü Etkinlik | Sayı | Süre (Saat) | Toplam İş Yükü (Saat) |
|---|---|---|---|
| Course Duration (Including the exam week: 16x Total course hours) | 16 | 2 | 32 |
| Mid-terms | 1 | 10 | 10 |
| Quiz | 2 | 15 | 30 |
| Assignment | 1 | 35 | 35 |
| Final examination | 1 | 20 | 20 |
| Toplam İş Yükü | 127 | ||
| Toplam İş Yükü / 25 (Saat) | 5,08 | ||
| Dersin AKTS Kredisi | 5 | ||