| Language of Instruction |
Türkçe |
| Course Type |
Elective Courses |
| Course Instructor(s) |
PROF. DR. SERVET ÜZTEMUR |
| Mode of Delivery |
Face-to-face. Online in mandatory cases. |
| Place of Delivery |
On Campus |
| Used Educational Platforms |
Online,Face-to-face |
| Prerequisites |
There is no prerequisite or co-requisite for this course. |
| Courses Recomended |
Scientific Research Methods, Quantitative Research Methods |
| Recommended Resources |
Field, A. (2018). Discovering statistics using IBM SPSS statistics (5th ed.). Sage.Gravetter, F. J., & Wallnau, L. B. (2017). Statistics for the behavioral sciences (10th ed.). Cengage Learning.Agresti, A., & Finlay, B. (2018). Statistical methods for the social sciences (5th ed.). Pearson.Büyüköztürk, Ş. (2023). Sosyal bilimler için veri analizi el kitabı (31. bs.). Pegem Akademi.Çokluk, Ö., Şekercioğlu, G., & Büyüköztürk, Ş. (2021). Sosyal bilimler için çok değişkenli istatistik: SPSS ve LISREL uygulamaları (6. bs.). Pegem Akademi.Howell, D. C. (2013). Statistical methods for psychology (8th ed.). Cengage Learning.Mertler, C. A., Vannatta Reinhart, R., & Cummings, K. D. (2021). Advanced and multivariate statistical methods: Practical application and interpretation (7th ed.). Routledge.Pallant, J. (2020). SPSS survival manual: A step by step guide to data analysis using IBM SPSS (7th ed.). McGraw-Hill Education.Tabachnick, B. G., & Fidell, L. S. (2019). Using multivariate statistics (7th ed.). Pearson. |
| Work Placement |
N/A |
| Aims of the Course |
The aim of this course is to ensure that doctoral students acquire theoretical knowledge and practical skills regarding basic and advanced quantitative data analysis methods used in scientific research processes. Within the scope of the course, it is intended that students develop their statistical thinking skills, be able to select statistical techniques appropriate to research problems, organize and analyze quantitative data, and interpret the findings in accordance with scientific criteria. In this regard, the course aims for students to comprehend the assumptions underlying common statistical methods—such as descriptive statistics, probability and sampling theory, hypothesis tests, analysis of variance (ANOVA), analysis of covariance (ANCOVA), chi-square tests, and regression analysis—to apply these methods to research data, and to utilize the results effectively in academic research. By the end of the course, students are expected to gain competence as researchers who can independently plan quantitative research, select appropriate analysis techniques, and make statistical inferences consistent with scientific publication standards. |