PSY5101 STATISTICS, METHODS, AND ETHICS IN PSYCHOLOGICAL RESEARCH
| Course Code: | 2335101 |
| METU Credit (Theoretical-Laboratory hours/week): | 4 (3.00 - 2.00) |
| ECTS Credit: | 10.0 |
| Department: | Psychology |
| Language of Instruction: | English |
| Level of Study: | Graduate |
| Course Coordinator: | Assist.Prof.Dr İLKER DALĞAR |
| Offered Semester: | Fall Semesters. |
Course Objectives
This course aims to equip you with a strong foundation in statistical thinking and application, emphasizing the ability to critically evaluate, select, and apply appropriate statistical methods in psychological research. You will develop skills to investigate a dataset, assess the assumptions underlying statistical tests, handle issues like missing data and outliers, and conduct commonly used statistical analyses, including t-tests, correlation, regression, ANOVA, and mixed models. Practical application through lab work provides you with hands-on experience on datasets using SPSS or JASP, advancing your ability to independently navigate real-world data analysis challenges. This will also enable you to interpret and report analysis results and have the confidence to self-learn new statistical methods.
Course Content
The aim of this course is to enable students to use several statistical techniques to analyze data with SPSS (Statistical Package for Social Sciences) program. The statistical techniques include t-test (independent and dependent), Chi-square, analysis of variance (ANOVA), techniques, MANOVA, correlation, regression, multiple regression, discriminant analysis and factor analysis
Course Learning Outcomes
By the end of this course, you will be able to:
- Develop statistical reasoning: Understand and explain key statistical concepts and terms, moving beyond memorized rules to rationalize their choice of statistical tests.
- Understand and assess data quality: Identify and handle common issues such as missing data, outliers, and violations of statistical assumptions.
- Choose appropriate statistical methods: Select and apply the correct statistical tests (e.g., t-tests, ANOVA, regression, mixed models) for various data types and research designs.
- Conduct statistical analyses: Gain hands-on experience with SPSS or JASP to analyze datasets, interpreting and reporting results accurately.
- Critically evaluate statistical methods: Analyze the pros and cons of various statistical techniques, considering the context of the research question.
- Engage with contemporary research practices: Become aware of current issues in the research world, including replicability, open science, and ethical considerations.
- Overall, improve scientific reasoning: Enhance their ability to think critically and systematically about the implications of statistical decisions in psychological research.
Program Outcomes Matrix
| Level of Contribution | |||||
| # | Program Outcomes | 0 | 1 | 2 | 3 |
| 1 | Skills to understand and successfully employ the latest and most advanced research and data analysis methods and techniques. | ✔ | |||
| 2 | Knowledge of the latest theoretical and empirical literature in psychology. | ✔ | |||
| 3 | Skills to conduct research and critically evaluate the important literature on any topic of interest related to psychology or other relevant disciplines. | ✔ | |||
| 4 | Awareness about the novel information in light of the theoretical knowledge gained and knowledge to develop advanced research topics and questions. | ✔ | |||
| 5 | Skills to develop and carry out a research project from beginning to end in light of the formulated research questions using the accumulated knowledge from relevant literature and methods. | ✔ | |||
| 6 | Awareness of conducting research, publishing, and application activities in light of ethical principles and values. | ✔ | |||
| 7 | Skills to work independently as an individual and as part of a team. | ✔ | |||
| 8 | Skills to communicate effectively, both in written and oral forms of English and Turkish, during scientific activities. | ✔ | |||
0: No Contribution 1: Little Contribution 2: Partial Contribution 3: Full Contribution