ANTALYA BİLİM UNIVERSITY
Course Information Package

PSYC 2002 - Statistics II

Basic Information

Course Code:
PSYC 2002
Course Name:
Statistics II
Language of Instruction:
English
Course Type:
Class
Course Level:
Bachelor
ECTS:
8.00
Instructor:
Dr. Öğr. Üyesi Demet KARA

Course Objectives

This course aims to increase students' statistical knowledge and applications through intermediate and advanced statistical analysis techniques.

Course Content

The course includes teaching basic and advanced quantitative research methods in psychology.

Prerequisites / Corequisites

PSYC 1004 and PSYC 2001

Course Books / Materials / Recommended Resources

Andy Field. Discovering statistics using IBM SPSS Statistics (4th Edition)

Learning Outcomes

Code Description
LO1 Conducting effective psychological research, creating theories, and scientifically testing hypotheses.
LO2 Learn various research method techniques and apply them to various research questions.
LO3 Have basic knowledge of data analysis.
LO4 Ability to enter data into SPSS, perform basic analysis, and interpret results.
LO5 Interpret results correctly

Weekly Course Content

Week Content
1 Review the Previous Term and the Course Schedule
2 Introduction to Regression
3 Basic and Multiple Regression
4 Basic and Multiple Regression
5 Repeated Measures ANOVA
6 ANCOVA and MANOVA
7 Mediation and Moderation
8 Mediation and Moderation
9 Mediation and Moderation
10 Presentation of Research Ideas and Examination
11 Factorial ANOVA
12 Factorial ANOVA
13 Factor Analysis
14 Factor Analysis
15 Review

Workload Calculation

Activity Count Duration (Hours) Total
Attendance 14 3.00 42.00
Practice 14 2.00 28.00
Pre-Class Individual Study 14 3.00 42.00
Post-Class Individual Study 14 3.00 42.00
Midterm Exam/Preparation 1 20.00 20.00
Final Exam/Preparation 1 20.00 20.00
Quiz Preparation 3 4.00 12.00
Homework 1 24.00 24.00
Research Presentation 1 5.00 5.00
Total Workload (Hours) 235
ECTS Credit (Workload / 25) 8

Assessment

# Assessment Type Contribution (%)
1 Midterm Exam %30
2 Quiz %10
3 Project %25
4 Final Exam %35
TOTAL %100

PO - LO Matrix

PO \ LO
LO1
LO2
LO3
LO4
LO5
PO-1
PO-2
PO-3
PO-4
PO-5
PO-6
PO-7
PO-8
PO-9
PO-10
PO-11
PO-12
PO-13
PO-14
PO-15
PO-16
1
Low Contribution
2
Medium Contribution
3
High Contribution

Teaching and Learning Methods

# Method Name Description Tools
1 Lecture (expository teaching), interactive discussion Listening and taking notes. Standard classroom technologies, multimedia tools (projector, computer, digital presentations)
2 Group Work Students determine the slope and cross-sectional geometric characteristics of a parabolic irrigation canal on campus, plot the flow rate curve at different sections of the canal, and submit a report. Land surveying instruments
3 Laboratory Listening, note-taking, conceptual analysis, critical thinking, questioning, and participation in discussions. Special equipment
4 Homework Solving and analyzing homework questions using a computer and Excel. Computer
5 Oral Research – lifelong learning, processing situations, developing questions, interpreting, presenting

Academic Integrity and Artificial Intelligence

Academic Integrity Policy on AI and Plagiarism: The use of Artificial Intelligence (AI) tools in writing assignments must be limited and responsible. Excessive reliance on AI-generated content (over 30%) and/or a similarity index above 30% in Turnitin will be considered violations of academic integrity. Consequences may include, but are not limited to:  (1) Reduction in grade (2) Non-evaluation of the homework/assignment (3) Referral for disciplinary action in accordance with university policies. Students are encouraged to use AI tools only as supportive resources (e.g., brainstorming, grammar checks) while ensuring that submitted work reflects their own original thinking and effort.