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| YBS3001 | Statistics | 3+0+0 | ECTS:3 | | Year / Semester | Fall Semester | | Level of Course | First Cycle | | Status | Compulsory | | Department | DEPARTMENT of MANAGEMENT INFORMATION SYSTEMS | | Prerequisites and co-requisites | None | | Mode of Delivery | Face to face, Practical | | Contact Hours | 14 weeks - 3 hours of lectures per week | | Lecturer | Doç. Dr. Burçin KURT | | Co-Lecturer | | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | Information about the concept of statistics, basic concepts and methods used in statistics are given and their use on data is explained. |
| Learning Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | LO - 1 : | Information about the basics of statistics. | 2 | 1,3,4,6, | | LO - 2 : | Interprets and shows graphically summary values for a data set. | 2 | 1,3,4,6, | | LO - 3 : | Learn to establish and test hypothesis. | 2 | 1,3,4,6, | | LO - 4 : | To be able to interpret the relationships with correlation analysis and regression and to make predictions or predictions about the subject by using this relationship. | 2 | 1,3,4,6, | | LO - 5 : | Performing applications with SPSS program. | 2 | 1,3,4,6, | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), LO : Learning Outcome | | |
| Definition, subject, aim and types of statistics, basic concepts about statistics, data sources and data collection techniques (data organization, graphs, means (central tendency measures), variability measures, skewness and kurtosis measures, some hypothesis tests, correlation analysis and simple regression. |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Definition of statistics and basic concepts of statistics | | | Week 2 | Definition of statistics and basic concepts of statistics | | | Week 3 | Data sources, data collection techniques | | | Week 4 | Graphical Display of Data | | | Week 5 | Measures of central tendency, skewness and kurtosis | | | Week 6 | Measures of central tendency, skewness and kurtosis | | | Week 7 | Some hypothesis tests | | | Week 8 | Midterm exam | | | Week 9 | Hypothesis testing with SPSS | | | Week 10 | Some hypothesis tests | | | Week 11 | Hypothesis testing with SPSS | | | Week 12 | Correlation analysis | | | Week 13 | Correlation analysis with SPSS | | | Week 14 | Simple regression analysis | | | Week 15 | Regression analysis with SPSS | | | Week 16 | Final Exam | | | |
| 1 | Vasif V. Nabiyev,2003, Yapay Zeka,Seçkin Yayıncılık | | | 2 | Hastie T, Tibshirani R, and Friedman J.,2009,The Elements of Statistical Learning: Data Mining, Inference, and Prediction (Second Edition),Springer | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 8 | | 90 | 50 | | Project | 16 | | | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 4 | 16 | 64 | | Arasınav | 2 | 1 | 2 | | Uygulama | 2 | 16 | 32 | | Ödev | 4 | 1 | 4 | | Total work load | | | 102 |
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