PSYC217 STATISTICS FOR PSYCHOLOGY II
| Course Code: | 3710217 |
| METU Credit (Theoretical-Laboratory hours/week): | 4 (3.00 - 2.00) |
| ECTS Credit: | 7.0 |
| Department: | Psychology |
| Language of Instruction: | English |
| Level of Study: | Undergraduate |
| Course Coordinator: | Assist.Prof.Dr GÜZEL MEHMET AKİF |
| Offered Semester: | Fall Semesters. |
Course Objectives
This course aims to teach how to approach data analysis and interpretation. Building upon the content of the PSYC 116, the course will teach students how to use an appropriate statistical analysis on a given dataset and how to use statistical software to conduct the statistical tests. Additionally, the course will teach how to generate APA-style tables and report the statistical results.
The theoretical sessions of the course will follow the content of the PSYC 116. After a brief refresher about the basic concepts such as probability, sample vs. population, t- and z-tests, the theoretical session will teach the assumptions and rationale of ANOVA tests, correlation and regression, and some of the non-parametric tests. The concepts of power, effect size, and confidence interval will be covered. Along with students, the teaching of the statistical tests will be reinforced by conducting hands-on statistical tests on various datasets.
The laboratory sessions of the course will focus on teaching how to use statistical packages to conduct statistical tests covered in the theoretical sessions in the same week and in previous weeks. The laboratory sessions aim to utilize JASP and/or SPSS. The laboratory sessions will teach students data entry, data analysis, interpretation of the results, and data/results presentation.
Course Content
This course is intended to introduce the methods of statistical hypothesis testing that are used frequently in more complex research designs in psychology. The main part of the course will cover the use of Analysis of Variance (ANOVA) in analyzing psychological data. In addition, the use of non-parametric tests and the issue of statistical power will be discussed
Course Learning Outcomes
By the end of the semester, students are expected to learn how to approach a dataset to conduct and report an appropriate statistical analysis on a given dataset with a basic understanding of the assumptions and rationale of the covered statistical tests.They will also learn how to conduct statistical analysis using a statistical package.
Program Outcomes Matrix
| Level of Contribution | |||||
| # | Program Outcomes | 0 | 1 | 2 | 3 |
| 1 | Solid background in basic theories and approaches in psychology | ✔ | |||
| 2 | Skills to follow both national and international publications and developments in the discipline and to obtain and interpret new information in the light of acquired theoretical knowledge | ✔ | |||
| 3 | Awareness of the value of continuing educational practices such as in-service trainings, seminars, and conferences to keep career-relevant knowledge and skills up-to-date | ✔ | |||
| 4 | Skills to conduct research based on basic knowledge related to testing and measurement, research methods, and statistics as well as the ability to present and disseminate research findings both orally and in writing | ✔ | |||
| 5 | Knowledge and skills about conducting research and practice by adhering to ethical guidelines | ✔ | |||
| 6 | Skills in oral and written communication both in Turkish and English as well as preferably learning a third language | ✔ | |||
| 7 | Skills to work in teams that involve disciplinary and interdisciplinary projects | ✔ | |||
| 8 | Critical thinking skills in following the psychological literature together with the psychology-related information appearing in popular media | ✔ | |||
| 9 | Skills to generate practical and culture-sensitive solutions to problems | ✔ | |||
| 10 | Awareness of societal, environmental, and economic factors in professional practice and research | ✔ | |||
| 11 | Skills to lead and pioneer in the profession of psychology, either in academia or professional practice | ✔ | |||
| 12 | Skills in independent and team work | ✔ | |||
0: No Contribution 1: Little Contribution 2: Partial Contribution 3: Full Contribution