Nevşehir Hacı Bektaş Veli University Course Catalogue
|
|||||
| Year/Semester of Study | 1 / Spring Semester | ||||
| Level of Course | 2nd Cycle Degree Programme | ||||
| Type of Course | Optional | ||||
| Department | EĞİTİMDE YAPAY ZEKA TEKNOLOJİLERİ(TEZLİ YÜKSEK LİSANS ÖNERİLEN) | ||||
| Pre-requisities and Co-requisites | None | ||||
| Mode of Delivery | Face to Face | ||||
| Teaching Period | 14 Weeks | ||||
| Name of Lecturer | ŞEYHMUS AYDOĞDU (saydogdu@nevsehir.edu.tr) | ||||
| Name of Lecturer(s) | |||||
| Language of Instruction | Turkish | ||||
| Work Placement(s) | None | ||||
| Objectives of the Course | |||||
| The aim of this course is to provide knowledge and skills regarding the basic concepts of statistical data analysis and the basic statistical operations to be performed on the data collected in a scientific research process. | |||||
| Learning Outcomes | PO | MME | |
| The students who succeeded in this course: | |||
| LO-1 | Can choose the statistical data analysis technique suitable for the research problem. |
PO-6 Plans and conducts scientific studies using research methods and techniques, independently or as a member of a team. PO-7 Develops and applies data collection tools in scientific research and analyzes the collected data with statistical methods. |
Examination Term Paper |
| LO-2 | Can report and interpret the findings obtained from data analysis. |
PO-6 Plans and conducts scientific studies using research methods and techniques, independently or as a member of a team. PO-7 Develops and applies data collection tools in scientific research and analyzes the collected data with statistical methods. |
Examination Term Paper |
| PO: Programme Outcomes MME:Method of measurement & Evaluation |
|||
| Course Contents | ||
| This course covers the basic concepts of statistical data analysis, choosing the appropriate analysis method for data analysis, introducing the SPSS Package application, performing descriptive analyzes, simple and partial correlation analysis, comparison of mean scores in unrelated measures, comparison of mean scores in related measures, average scores in mixed measures. comparison, simple and multiple regression analysis, covariance analysis, factor analysis, non-parametric statistics and some statistical analyzes used in validity and reliability analysis. | ||
| Weekly Course Content | ||
| Week | Subject | Learning Activities and Teaching Methods |
| 1 | Scientific research stages, identifying research problems, overview of data analysis | Lecture, Discussion, Concept Mapping, Group Work |
| 2 | Types of descriptive analysis, reporting descriptive statistics | Applied Lecture, Individual Study, SPSS Practice |
| 3 | Correlation: simple and partial. Meaning, computation and interpretation | Problem Solving, Applied Practice, Case Study |
| 4 | Independent samples t-test: assumptions, steps, interpretation | Lecture, SPSS Practice, Matching Activity |
| 5 | Practice tasks with independent samples and report writing | Practical Task, Peer Evaluation, Reporting |
| 6 | Dependent samples t-test: assumptions, application | Applied Lecture, Q&A, SPSS Application |
| 7 | Practice on paired comparisons, interpretation and presentation | Peer Presentation, Feedback, Analysis Presentation |
| 8 | mid-term exam | |
| 9 | Comparison of mixed measures (e.g. repeated measures ANOVA) | Lecture, SPSS Practice, Small Group Practice |
| 10 | Simple regression: variable relationships, regression line | Lecture, Practice, Real Data Analysis |
| 11 | Multiple regression: model building and assumption checking | Practice, Discussion, Model Comparison |
| 12 | ANCOVA: effect of covariates, adjusted means | Lecture, SPSS Practice, Application Report |
| 13 | Factor analysis: variable reduction, construct validity | Applied Lecture, Exploration, SPSS Analysis |
| 14 | Non-parametric tests: Mann-Whitney U, Wilcoxon, Kruskal-Wallis | Comparative Practice, Interpretation Activity |
| 15 | Reliability and validity statistics: Cronbach Alpha, KMO, Bartlett | Presentation, Practice, Peer Review |
| 16 | final exam | |
| Recommend Course Book / Supplementary Book/Reading | ||
| 1 | Büyüköztürk, Ş. (2023) Sosyal Bilimler için Veri Analizi El Kitabı İstatistik, Araştırma Deseni SPSS Uygulamaları ve Yorum. Pegem Akademi: Ankara. | |
| 2 | Can, A. (2022). SPSS ile Bilimsel Araştırma Sürecinde Nicel Veri Analizi. Pegem Akademi: Ankara. | |
| 3 | Field, A. (2017). Discovering Statistics Using IBM SPSS Statistics. Sage Publications. | |
| Required Course instruments and materials | ||
| Textbook, Laptop | ||
| Assessment Methods | |||
| Type of Assessment | Week | Hours | Weight(%) |
| mid-term exam | 8 | 2 | 40 |
| Other assessment methods | |||
| 1.Oral Examination | |||
| 2.Quiz | |||
| 3.Laboratory exam | |||
| 4.Presentation | |||
| 5.Report | |||
| 6.Workshop | |||
| 7.Performance Project | |||
| 8.Term Paper | 16 | 1 | 30 |
| 9.Project | |||
| final exam | 16 | 1 | 30 |
| Student Work Load | |||
| Type of Work | Weekly Hours | Number of Weeks | Work Load |
| Weekly Course Hours (Theoretical+Practice) | 3 | 14 | 42 |
| Outside Class | |||
| a) Reading | 3 | 14 | 42 |
| b) Search in internet/Library | 3 | 14 | 42 |
| c) Performance Project | 0 | ||
| d) Prepare a workshop/Presentation/Report | 2 | 14 | 28 |
| e) Term paper/Project | 0 | ||
| Oral Examination | 0 | ||
| Quiz | 0 | ||
| Laboratory exam | 0 | ||
| Own study for mid-term exam | 3 | 7 | 21 |
| mid-term exam | 2 | 1 | 2 |
| Own study for final exam | 0 | ||
| final exam | 3 | 1 | 3 |
| 0 | |||
| 0 | |||
| Total work load; | 180 | ||