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PSY201 – Statistics in Psychology II

Bachelor of Science in Psychology

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Core Course

PSY201 – Statistics in Psychology II

Course Unit Code: PSY201

Type Of Unit: Compulsory 

Level of Course Unit: Undergraduate

Year of Study: Year 2

Semester: Semester 1

Number of ECTS Credits: 7.5

Class Contact Hours: 36

Mode of Delivery

Face to Face

Prerequisites

PSY202 & PSY203 

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The purpose of this course is to provide students with a more in-depth and sophisticated grasp of statistical techniques as they are used in psychological research. This course aims to give students the abilities and information necessary to critically examine and interpret complicated data sets in the field of psychology by building on the fundamental ideas covered in “Statistics in Psychology I.” The course aims to improve students‘ abilities to conduct rigorous and significant research, make wise decisions based on data analysis, and contribute to the development of psychology science by exploring more complex statistical approaches.

Learning Outcomes

The following learning outcomes are expected, where students will be able to:  

  1. Describe the fundamental ideas and assumptions of advanced statistical methods used in psychological research. 
  2. Apply advanced statistical procedures to examine intricate psychological data sets. 
  3. Interpret the results of complex statistical analyses, including statistical significance and effect sizes. 
  4. Evaluate research articles that use advanced statistical techniques, noting their strengths and limitations. 
  5. Adhere to ethical principles and responsible practices in psychological statistics analysis. 

Students will acquire a more in-depth and sophisticated grasp of statistical techniques as they are used in psychological research. This course aims to give students the abilities and information necessary to critically examine and interpret complicated data sets in the field of psychology by building on the fundamental ideas covered in “Statistics in Psychology I.” The course aims to improve students’ abilities to conduct rigorous and significant research, make wise decisions based on data analysis, and contribute to the development of psychology science by exploring more complex statistical approaches.

Module 1: Review and Foundations

Module 2: Multivariate Analysis Techniques

Module 3: Non-Parametric Methods

Module 4: Interaction Effects and Advanced ANOVA

Module 5: Advanced Correlation Techniques

Module 6: Hierarchical Linear Models (HLM)

Module 7: Ethical Considerations and Responsible Analysis

Module 8: Data Management and Preprocessing

Module 9: Practical Applications and Case Studies

Module 10: Emerging Trends and Future Directions

Course Features

Teaching methodology: Lecture and labs

Assessment:

  1. Midterm & Final Exam (30% & 30%): Mid-term and final exams will be conducted covering the entire course. Both exams will include multiple-choice, short-answer, and essay questions. 
  2. Group assignment (20%), where students are required to apply advanced statistical techniques to real data. 
  3. Individual in-class hand-on assignment (5%), where students will be asked to perform specific analyses using statistical software.  
  4. Individual assignment (5%), where students will critically assess research articles that utilize advanced statistics. 
  5. Presence and Participation (10%): Students should be present and actively participate in in-class discussions. 

Readings

  1. Tabachnick, B. G., & Fidell, L. S. (2019). Using Multivariate Statistics. Pearson. 
  2. Field, A. (2018). Discovering Statistics Using IBM SPSS Statistics. SAGE Publications. 

Call Center

CYPRUS

GREECE

INTERNATIONAL

Request Information Request Information ⟶

Informed Consent Form

Dear Participant,

You are invited to participate in a survey as part of the DiFiCy – Digital Transformation and FinTech: Shaping Cyprus’s Economy research project which is implemented by the University of Limassol, PwC Cyprus and Unity Growth Limited.

The project is co-funded by the European Union within the framework of the Cohesion Policy Programme “THALIA 2021-2027” through the Research and Innovation Foundation (RIF) in Cyprus [Pr. number: EXCELLENCE/0524/0568].

The study has been approved by the National Bioethics Committee of Cyprus (Approval no.: EEBK EΠ 2025.01.19 )

This project explores digital transformation and FinTech adoption in Cyprus, with a particular focus on SMEs and the broader business ecosystem. It uses a mixed-methods research design, combining survey data with interviews and case study evidence to generate evidence-based insights for policymakers and businesses.

Before deciding whether to participate, please read the following information carefully.

Purpose of Participation

The purpose of this research is to better understand the drivers, challenges, and impacts of digital transformation and FinTech adoption in Cyprus. The findings aim to support evidence-based policymaking, strengthen business practices, and contribute to innovation and economic development.

Your participation involves the following:

Completion of this survey, which takes approximately 15 minutes.

Invitation to take part in an optional interview.

Contribution to a case study or discussion session at a later stage.

Your participation is entirely voluntary, and you are free to decline or withdraw at any time without any consequences.

If you wish to withdraw from the study after submitting your responses, you may do so by contacting the Project Coordinator.

Data Confidentiality and Usage

All data collected will be handled in strict accordance with the General Data Protection Regulation (GDPR) and Cyprus Data Protection Law (125(I)/2018).

Your data will be treated confidentially, pseudonymised and anonymised, and no personally identifiable information will be disclosed. Data will be securely stored and accessed only by authorised members of the research team. In some cases, qualitative data may be processed using machine learning techniques, such as keyword identification or pattern detection, strictly to support analysis; however, all interpretation and conclusions will be made by the researchers.

Aggregated and anonymised findings derived from the data (e.g., statistical summaries, graphs, and thematic insights) may be used for dissemination activities, including scientific publications, policy reports, infographics, and training materials. These outputs will not contain any information that could directly or indirectly identify participants or their organisations.

Anonymised data may be shared publicly after a 24-month embargo period, while raw or sensitive data will not be publicly available. Access to raw or sensitive data will be granted only upon justified request and consortium approval.

Your participation in this study does not involve any risks.

On the contrary, your contribution may help improve digital and FinTech policies, support SME development and innovation strategies, and enhance the overall business environment in Cyprus.

Contact Information

If you have any questions, concerns, withdraw requests or complaints, please contact the Project Coordinator, Dr. Snezana Eminidou. Please include “DiFiCy Survey” in the subject line.

Email: snezana@uol.ac.cy

Phone number: +357 22462228

Partnership:

Thank you for your valuable contribution to this research.

The project is co-funded by the EU within the framework of the Cohesion Policy Programme “THALIA 2021-2027” through the Research and Innovation Foundation. [Pr. no. EXCELLENCE/0524/0568]. The content reflects the views of the author(s) only. The European Commission and the Managing Authority of THALIA 2021–2027 cannot be held responsible for any use which may be made of the information contained therein.