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| EKO4002 | Computer Applications in Statistics - II | 3+0+0 | ECTS:6 | | Year / Semester | Spring Semester | | Level of Course | First Cycle | | Status | Compulsory | | Department | DEPARTMENT of ECONOMETRICS | | Prerequisites and co-requisites | None | | Mode of Delivery | | | Contact Hours | 14 weeks - 3 hours of lectures per week | | Lecturer | Doç. Dr. Sinem KOÇAK | | Co-Lecturer | Asst. Prof. Dr. Uğur Şevik | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | By using the SPSS package program, the aim is to provide students with the ability to choose and use methods such as regression analysis, variance analysis, correlation analysis, factor analysis and cluster analysis that are suitable for the problem, analyze, interpret the results and write a report on the results. |
| Learning Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | LO - 1 : | perform operations on the mean tests for parametric and non-parametric | 1 - 2 - 3 | 1, | | LO - 2 : | apply variance analysis | 1 - 2 - 3 | 1, | | LO - 3 : | interpret relationships between variables using correlation analysis | 1 - 2 - 3 | 1, | | LO - 4 : | select appropriate statistical analysis method for a research | 1 - 2 - 3 | 1, | | LO - 5 : | perform statistical analysis appropriate to the problem using the SPSS package program | 1 - 2 - 3 | 1, | | 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 | | |
| This course covers theoretical knowledge and SPSS applications of methods such as prediction with regression analysis, analysis of variance, correlation analysis, The mean test for parametric and non-parametric technic |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Testing the difference between two population means (Independent samples) | | | Week 2 | Testing the difference between two population means (dependent samples) | | | Week 3 | Mean Tests (for Non-parametric) | | | Week 4 | Mann-Whitney U Test ve Wilcoxon İşareti Test | | | Week 5 | Comparing more than two population means (Parametric Tests) | | | Week 6 | One-way Analysis of Variance | | | Week 7 | Two-Way Analysis of Variance (non-interactional) | | | Week 8 | Two-Way Analysis of Variance (Interactional) | | | Week 9 | Midterm Exam | | | Week 10 | Repeated Measures One-way Anova test | | | Week 11 | Friedman and Wilcoxon testi | | | Week 12 | Cochran Q test | | | Week 13 | Chi-Squared test | | | Week 14 | Correlation Analysis | | | Week 15 | Regession Analysis | | | Week 16 | Final exam | | | |
| 1 | Lorcu, Fatma2020; Örneklerle veri analizi SPSS Uygulamalı, Detay Yayıncılık, İstanbul | | | |
| 1 | Balcı, S., Ahi, B. 2016; SPSS Kullanma Kılavuzu: SPSS ile Adım Adım Veri Analizi, Anı Yayıncılık, İstanbul | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | 04/2024 | 1 | 50 | | End-of-term exam | 16 | 06/2024 | 1 | 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 | 3 | 14 | 42 | | Sınıf dışı çalışma | 4 | 14 | 56 | | Arasınav için hazırlık | 6 | 3 | 18 | | Arasınav | 1 | 1 | 1 | | Uygulama | 3 | 14 | 42 | | Dönem sonu sınavı için hazırlık | 5 | 4 | 20 | | Dönem sonu sınavı | 1 | 1 | 1 | | Total work load | | | 180 |
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