PSY531 Advanced Research Methods and Statistics
PSY531 Advanced Research Methods and Statistics
Syllabus | International University of Sarajevo - Last Update on Sep 09, 2026
Syllabus Quick Jump
Search and navigate to any syllabus instantly
Psychology
Christian Valt
Course Lecturer
Course Objectives
This course provides students with an overview of the methods employed in the scientific investigation of psychological constructs. Students will learn how to design experiments to address scientific questions, and perform appropriate statistical analyses to draw reliable and meaningful conclusions. Through practical work, students will learn how to carry out experiments and evaluate the strengths and limitations of experimental findings. These skills are essential for evaluating literature and applying scientific thinking and critical reasoning in academic and everyday contexts. The course will also develop students' academic and professional writing skills. Students will learn how to communicate effectively in academic, professional, and workplace settings, including when interacting with experts in medicine and related scientific disciplines.
Learning Outcomes
After successful completion of the course, the student will be able to:
Course Materials
Required Textbook
Hugh Coolican, 2024, Research Methods and Statistics in Psychology, 8th edition. Routledge Publishing.
Additional Literature
Shelley H. Carson. 2012 Writing for Psychology, A guide for psychology concentrators. Harvard College Publications.Teaching Methods
Course delivery will be via lecture
Practice with statistical analysis using computer software
And writing exercises.
Weekly Topics
| Week | Topic | Readings / References |
|---|---|---|
| 1 | Introduction, syllabus presentation, course presentation | |
| 2 | Methods: Psychological variable and research methods | Chapter 2 |
| 3 📍 | Methods: Experiments and experimental designs in psychology research | Chapter 3 |
| 4 | Methods: Validity in psychological research | Chapter 4 |
| 5 | Ethical issues in psychology research | Chapter 21 |
| 6 | Planning a study and writing up a report | Chapter 26 |
| 7 | Do's and Don'ts in academic writing | |
| 8 | Midterm Exam | |
| 9 | Discussion of the research projects | |
| 10 | Statistics: data and descriptive statistics | Chapter 11 |
| 11 | Statistics: graphs and distributions | Chapters 12-13 |
| 12 | Statistics: Comparing two means | Chapter 17 |
| 13 | Statistics: Comparing several means | Chapters 22-23-24 |
| 14 | Statistics: Correlations and regressions | Chapters 19-20 |
| 15 | Publishing guidelines |
Course Schedule (All Sections)
| Section | Type | Day 1 | Venue 1 | Day 2 | Venue 2 |
|---|---|---|---|---|---|
| PSY531.1 | Course | Monday 17:00 - 19:50 | A F1.3 - Computer Lab | Monday 17:00 - 19:50 | A F2.8 - Classroom |
Office Hours & Room
Assessment Methods and Criteria
Assessment Components
Final exam
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3
Midterm exam
AI: Not AllowedAlignment with Learning Outcomes : 2 3
Research proposal
AI: Not AllowedAlignment with Learning Outcomes : 4 5
Homeworks
AI: Not AllowedAlignment with Learning Outcomes : 2 4
Research activity and active contribution
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3
IUS Grading System
| Grading Scale | IUS Grading System | IUS Coeff. | Letter (B&H) | Numerical (B&H) |
|---|---|---|---|---|
| 0 - 44 | F | 0 | F | 5 |
| 45 - 54 | E | 1 | ||
| 55 - 64 | C | 2 | E | 6 |
| 65 - 69 | C+ | 2.3 | D | 7 |
| 70 -74 | B- | 2.7 | ||
| 75 - 79 | B | 3 | C | 8 |
| 80 - 84 | B+ | 3.3 | ||
| 85 - 94 | A- | 3.7 | B | 9 |
| 95 - 100 | A | 4 | A | 10 |
Late Work Policy
Information about late submission policies will be shared during class and posted in this section. Please check back for official guidelines.
ECTS Credit Calculation
📚 Student Workload
This 6 ECTS credit course corresponds to 150 hours of total student workload, distributed as follows:
Lecture
45 hours ⏳ (15 week × 3 h)
Midterm Exam Study
24 hours ⏳ (4 week × 6 h)
Final Exam Study
36 hours ⏳ (6 week × 6 h)
Research Proposal
25 hours ⏳ (5 week × 5 h)
Homework
10 hours ⏳ (5 week × 2 h)
Research activities and active contribution
10 hours ⏳ (5 week × 2 h)
150 Total Workload Hours
6 ECTS Credits
Course Policies
Academic Integrity
All work submitted must be your own. Plagiarism, cheating, or any form of academic dishonesty will result in disciplinary action according to university policies. When in doubt about citation practices, consult the instructor.
Attendance Policy
Students are expected to adhere to the attendance requirements as outlined in the International University of Sarajevo Study Rules and Regulations. Excessive absences, whether excused or unexcused, may impact academic performance and eligibility for assessment. Mandatory sessions (e.g., labs, workshops) require attendance unless formally exempted. For detailed policies on absences, documentation, and penalties, please refer to the official university regulations.
Technology & AI Policy
Laptops/tablets may be used for note-taking only during lectures. Phones should be silenced and put away during all class sessions. Audio/video recording requires prior permission from the instructor.
Artificial Intelligence (AI) Usage: The use of AI tools (e.g., ChatGPT, Copilot, Gemini) varies by assessment component. Please refer to the AI usage indicator next to each assessment item in the Assessment Methods and Criteria section above. Submitting AI-generated content as your own work, where AI is not explicitly allowed, constitutes an academic integrity violation.
Communication Policy
All course-related communication should occur through official university channels (institutional email or SIS). Emails should include [PSY531] in the subject line.
Academic Quality Assurance Policy
Course Academic Quality Assurance is achieved through Semester Student Survey. At the end of each academic year, the institution of higher education is obliged to evaluate work of the academic staff, or the success of realization of the curricula.
Learning Tips
Be prepared to contribute thoughtfully during class discussions, labs, or collaborative work. Active participation deepens understanding and encourages critical thinking.
Complete assigned readings or prep materials before class. Take notes, highlight key ideas, and jot down questions. Aim to grasp core concepts and their applications—not just facts.
Use course frameworks or methodologies to analyze problems, case studies, or projects. Begin early to allow time for reflection and refinement. Seek feedback to improve your work.
Don’t hesitate to reach out when something is unclear. Use office hours, discussion boards, or peer networks to clarify concepts and stay on track.
Syllabus Last Updated on Sep 09, 2026 | International University of Sarajevo
Print Syllabus
Referencing Curricula Print this page
| Course Code | Course Title | Weekly Hours* | ECTS | Weekly Class Schedule | ||||||
| T | P | |||||||||
| PSY531 | Advanced Research Methods and Statistics | 3 | 0 | 6 | Mondays 17:00 - 19:50 | |||||
| Prerequisite | PSY105 | It is a prerequisite to | - | |||||||
| Lecturer | Christian Valt | Office Hours / Room / Phone | Currently not available |
|||||||
| cvalt@ius.edu.ba | ||||||||||
| Assistant | Assistant E-mail | |||||||||
| Course Objectives | This course provides students with an overview of the methods employed in the scientific investigation of psychological constructs. Students will learn how to design experiments to address scientific questions, and perform appropriate statistical analyses to draw reliable and meaningful conclusions. Through practical work, students will learn how to carry out experiments and evaluate the strengths and limitations of experimental findings. These skills are essential for evaluating literature and applying scientific thinking and critical reasoning in academic and everyday contexts. The course will also develop students' academic and professional writing skills. Students will learn how to communicate effectively in academic, professional, and workplace settings, including when interacting with experts in medicine and related scientific disciplines. | |||||||||
| Textbook | Hugh Coolican, 2024, Research Methods and Statistics in Psychology, 8th edition. Routledge Publishing. | |||||||||
| Additional Literature |
|
|||||||||
| Learning Outcomes | After successful completion of the course, the student will be able to: | |||||||||
|
||||||||||
| Teaching Methods | Course delivery will be via lecture, practice with statistical analysis using computer software, and writing exercises. | |||||||||
| Teaching Method Delivery | Face-to-face | Teaching Method Delivery Notes | ||||||||
| WEEK | TOPIC | REFERENCE | ||||||||
| Week 1 | Introduction, syllabus presentation, course presentation | |||||||||
| Week 2 | Methods: Psychological variable and research methods | Chapter 2 | ||||||||
| Week 3 | Methods: Experiments and experimental designs in psychology research | Chapter 3 | ||||||||
| Week 4 | Methods: Validity in psychological research | Chapter 4 | ||||||||
| Week 5 | Ethical issues in psychology research | Chapter 21 | ||||||||
| Week 6 | Planning a study and writing up a report | Chapter 26 | ||||||||
| Week 7 | Do's and Don'ts in academic writing | |||||||||
| Week 8 | Midterm Exam | |||||||||
| Week 9 | Discussion of the research projects | |||||||||
| Week 10 | Statistics: data and descriptive statistics | Chapter 11 | ||||||||
| Week 11 | Statistics: graphs and distributions | Chapters 12-13 | ||||||||
| Week 12 | Statistics: Comparing two means | Chapter 17 | ||||||||
| Week 13 | Statistics: Comparing several means | Chapters 22-23-24 | ||||||||
| Week 14 | Statistics: Correlations and regressions | Chapters 19-20 | ||||||||
| Week 15 | Publishing guidelines | |||||||||
| Assessment Methods and Criteria | Evaluation Tool | Quantity | Weight | Alignment with LOs | AI Usage |
| Final exam | 1 | 30 | 1, 2, 3 | Not Allowed | |
| Semester Evaluation Components | |||||
| Midterm exam | 1 | 20 | 2, 3 | Not Allowed | |
| Research proposal | 1 | 30 | 4, 5 | Not Allowed | |
| Homeworks | 5 | 10 | 2, 4 | Not Allowed | |
| Research activity and active contribution | 1 | 10 | 1, 2, 3 | Not Allowed | |
| *** ECTS Credit Calculation *** | |||||
| Activity | Hours | Weeks | Student Workload Hours | Activity | Hours | Weeks | Student Workload Hours | |||
| Lecture | 3 | 15 | 45 | Midterm Exam Study | 6 | 4 | 24 | |||
| Final Exam Study | 6 | 6 | 36 | Research Proposal | 5 | 5 | 25 | |||
| Homework | 2 | 5 | 10 | Research activities and active contribution | 2 | 5 | 10 | |||
| Total Workload Hours = | 150 | |||||||||
| *T= Teaching, P= Practice | ECTS Credit = | 6 | ||||||||
| Course Academic Quality Assurance: Semester Student Survey | Last Update Date: 28/09/2026 | |||||||||