Rapor Tarihi: 20.12.2025 01:46
| Course Title | Code | Language | Type | Semester | L+U Hour | Credits | ECTS |
|---|---|---|---|---|---|---|---|
| Statistics | YBS156 | Turkish | Compulsory | 2. Semester | 3 + 0 | 3.0 | 6.0 |
| Prerequisite Courses | |
| Course Level | Undergraduate |
| Mode of delivery | face to face |
| Course Coordinator | Prof. Dr. Hakan Murat ARSLAN |
| Instructor(s) | |
| Goals | In the statistics course, the main purpose is to make predictions about the future using numerical data and to understand and interpret the analysis outputs. In the course, in which basic statistics concepts will be taught together with case studies, it is aimed that students will understand statistical methods and acquire the ability to use the appropriate data analysis method. |
| Course Content | Introduction to Statistics and Basic Concepts Frequency Distributions (Histograms, Frequency Polygons) Averages (Arithmetic, Geometric, Squared and Harmonic) Other Measures of Central Tendency (Mode, Median, and Quartiles) Standard Deviation and Mean Deviation (Excel and SPSS Applications) Other Measures of Dispersion (Coefficient of Variation and Adjusted Variance) moments Skewness, Kurtosis and SPSS Applications Permutation and Current Applications Combination and Current Applications Probability Theory and Its Applications in Social Sciences Binomial Distribution and Applications Poisson Distribution and Applications Normal Distribution and SPSS Applications |
| # | Öğrenme Kazanımı |
| 1 | Defining the basic data structures in obtaining the necessary information in decision problems and revealing their differences. |
| 2 | To reveal the tools and methods of summarizing and classifying statistical data. |
| 3 | To apply statistical approach in the process of producing information. |
| 4 | Defining the basic concepts of statistics |
| 5 | To be able to statistically analyze decision problems related to social sciences. |
| 6 | To reveal the relationships between the variables in the phenomena.. |
| Week | Topics/Applications | Method |
|---|---|---|
| 1. Week | Introduction to Statistics and Basic Concepts | Research |
| 2. Week | Frequency Distributions (Histograms, Frequency Polygons) | |
| 3. Week | Averages (Arithmetic, Geometric, Squared and Harmonic) | Research |
| 4. Week | Other Measures of Central Tendency (Mode, Median and Quartiles) | Research |
| 5. Week | Standard Deviation and Mean Deviation (Excel and SPSS Applications) | Research |
| 6. Week | Other Measures of Spread (Coefficient of Change and Adjusted Variance) | Research |
| 7. Week | Moments | Research |
| 8. Week | Skewness, Kurtosis and SPSS Applications | Research |
| 9. Week | Permutation and Current Applications | Research |
| 10. Week | Combination and Current Applications | Research |
| 11. Week | Probability Theory and Applications in Social Sciences | Research |
| 12. Week | Binomial Distribution and Applications | Research |
| 13. Week | Poisson Distribution and Applications | Research |
| 14. Week | Normal Distribution and SPSS Applications | Research |
| No | Program Requirements | Level of Contribution | |||||
|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | Graduates will have a holistic perspective on business functions | ✔ | |||||
| 2 | Graduates will have conceptual knowledge in the field of informatics in the sector average. | ✔ | |||||
| 3 | Graduates may integrate the business functions and IT infrastructure | ✔ | |||||
| 4 | Graduates will have awareness and knowledge about the processes of analyzing, designing, developing, and using information systems. | ✔ | |||||
| 5 | Students will have the ability to define the problem, collect data, analyze, interpret, evaluate, and develop a solution proposal for the solution of problems encountered in business. | ✔ | |||||
| 6 | Graduates may develop new strategic approaches for the efficiency of applications used in businesses. | ✔ | |||||
| 7 | Graduates may understand the logic of the algorithm and convert the designed algorithm into an up-to-date programming language. | ✔ | |||||
| 8 | Gradutes may have basic knowledge and understanding in the field of data science. | ✔ | |||||
| 9 | Graduates may have basic knowledge and understanding in the field of data science. | ✔ | |||||
| 10 | Graduates may base their vision on continuous learning and renewal. | ✔ | |||||
| 11 | Graduates may have an awareness of ethical and professional responsibility in business life. | ✔ | |||||
| 12 | Graduates may have an awareness of the individual and social effects of informatics applications and their legal consequences. gets the awareness of social responsibility. | ✔ | |||||
| 13 | Graduates may be able to use at least one foreign language in written and oral communication in the fields of information systems and business administration. | ✔ | |||||
| 14 | Graduates may take responsibility as an individual or team member in solving problems encountered in business life. | ✔ | |||||
| Program Requirements | DK1 | DK2 | DK3 | DK4 | DK5 | DK6 |
|---|---|---|---|---|---|---|
| PY1 | 4 | 3 | 4 | 4 | 4 | 3 |
| PY2 | 3 | 4 | 4 | 3 | 4 | 3 |
| PY3 | 5 | 4 | 4 | 5 | 3 | 3 |
| PY4 | 5 | 4 | 4 | 5 | 3 | 3 |
| PY5 | 5 | 4 | 4 | 4 | 4 | 3 |
| PY6 | 3 | 4 | 4 | 5 | 3 | 3 |
| PY7 | 3 | 4 | 4 | 4 | 4 | 3 |
| PY8 | 4 | 5 | 4 | 5 | 4 | 4 |
| PY9 | 3 | 4 | 3 | 4 | 4 | 4 |
| PY10 | 3 | 3 | 3 | 4 | 3 | 3 |
| PY11 | 5 | 4 | 4 | 3 | 4 | 4 |
| PY12 | 4 | 4 | 4 | 4 | 3 | 4 |
| PY13 | 4 | 3 | 4 | 3 | 4 | 4 |
| PY14 | 3 | 4 | 2 | 3 | 4 | 3 |
| Ders Kitabı veya Notu |
|
|---|---|
| Diğer Kaynaklar |
|
| ECTS credits and course workload | Quantity | Duration (Hour) | Total Workload (Hour) | |
|---|---|---|---|---|
|
Ders İçi |
Class Hours | 14 | 3 | 42 |
|
Ders Dışı |
Research | 7 | 3 | 21 |
| Other Activities | 14 | 2 | 28 | |
|
Sınavlar |
Midterm 1 | 1 | 1 | 1 |
| Homework 1 | 1 | 30 | 30 | |
| Homework 2 | 1 | 30 | 30 | |
| Final | 1 | 1 | 1 | |
| Total Workload | 153 | |||
| *AKTS = (Total Workload) / 25,5 | ECTS Credit of the Course | 6.0 | ||
