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SECTION I: GENERAL INFORMATION ABOUT THE COURSE

Course Code Course Name Year Semester Theoretical Practical Credit ECTS
60542METOZ-PSK0063 Statistical Methods in Psychology I 2 Fall 2 1 3 6
Course Type : Compulsory
Cycle: Bachelor      TQF-HE:6. Master`s Degree      QF-EHEA:First Cycle      EQF-LLL:6. Master`s Degree
Language of Instruction: Turkish
Prerequisities and Co-requisities: N/A
Mode of Delivery: Face to face
Name of Coordinator: Dr. Öğr. Üyesi HANDAN NOYAN
Dersin Öğretim Eleman(lar)ı: Dr. Öğr. Üyesi HANDAN NOYAN
Doçent Dr. FATMA ÖZGE BARUÖNÜ
Dersin Kategorisi: Programme Specific

SECTION II: INTRODUCTION TO THE COURSE

Course Objectives & Content

Course Objectives: .
The aim of the course is to introduce descriptive statistics such as data collection, purification, visualization, standard deviation, normal distribution, and inferential statistics such as correlation analysis. In addition, the course aims to introduce SPSS statistical program and its basic use.
Course Content: By introducing descriptive and inferential statistics terms and methods used in psychology research fields; concepts such as data types, central tendency and distribution measures, sample, population, statistical estimation and statistical hypothesis estimations will be discussed.

Course Learning Outcomes (CLOs)

Course Learning Outcomes (CLOs) are those describing the knowledge, skills and competencies that students are expected to achieve upon successful completion of the course. In this context, Course Learning Outcomes defined for this course unit are as follows:
Knowledge (Described as Theoritical and/or Factual Knowledge.)
  1) Explains basic statistical concepts and methods.
Skills (Describe as Cognitive and/or Practical Skills.)
  1) Determines the statistical analysis methods suitable for the research question.
  2) Makes simple statistical measurements such as calculating central tendency and distribution measures.
Competences (Described as "Ability of the learner to apply knowledge and skills autonomously with responsibility", "Learning to learn"," Communication and social" and "Field specific" competences.)
  1) Recognizes the computer programs used in data analysis.
  2) Knows processes of application of descriptive and hypothesis tests

Weekly Course Schedule

Week Subject
Materials Sharing *
Related Preparation Further Study
1) Introduction to Statistics : Definition and Functions of Statistics: Descriptive-Descriptive Statistics and Inferential Statistics
2) Statistics in Research Process: General Concepts and Terminology: Research Question, Research Problem, Hypothesis, Research Variables, Operational Definition.
3) Sampling, Classification of Variables, and Measurement Levels.
4) Normal Distribution, Central Tendency and Central Distribution Measurements.
5) Process of Hypothesis Testing : Definition of Research and Null Hypothesis, Alfa (Type I) and Beta (Type II) Errors, Confidence Level, Confidence Interval, Power of Test, and Decision of Hypothesis Test.
6) Statistics in Research Process: Asking a Research Question, Suggesting a Hypothesis, Definition the Variables, and Operational Definition the Variables, Definition of Measurement Levels, Definition of Process of Hypothesis Testing.
7) Experimental Designs and Choosing of the Correct Statistical Test for Data Analysis
8) Midterm
9) Introduction to Data Analysis on SPSS: Introduce the SPSS Interface, SPSS Data Entry, Practical Applications of the SPSS Program.
10) Frequency Distribution, Average, Mode and Median Calculations, Graphic Presentations, and Applications of Descriptive Statistic Test (Chi-Square Analysis) on the SPSS Program.
11) Testing of Normal Distribution and Correlation Analyses on the SPSS Program
12) Applications of the Parametric and Non-Parametric Two-Samples Hypothesis Tests on the SPSS Program.
13) One-Way ANOVA on the SPSS Program.
14) General Review and Applications on the SPSS Program
15) Final Examination
*These fields provides students with course materials for their pre- and further study before and after the course delivered.

Recommended or Required Reading & Other Learning Resources/Tools

Course Notes / Textbooks: Gravetter F & Wallnau L. (2011) Essentials of Statistics for the Behavioral Sciences (7th ed.) Wadsworth

Hovardaoğlu, S. (1994). Davranış Bilimleri İçin İstatistik, Hatiboğlu Yayınları-Ankara

Howell, D.C. (1989). Fundamental Statistics for the Behavioral Sciences, 2nd. Ed., PWS-Kent Publishing Company-Boston.

References: Temel Ders Kaynakları (2021 Güz)
1. SPSS Kullanma Kılavuzu: SPSS ile Adım Adım Veri Analizi (2016), Julie PALLANT (Çev: Doç. Dr. Sibel BALCI, Yrd. Doç. Dr. Berat AHİ), Anı Yayıncılık.
2. Sosyal Bilimler İçin Veri Analizi El Kitabı (2017), Doç. Dr. Şener BÜYÜKÖZTÜRK, Pegem Akademi Yayıncılık.

Blalock, H.M., Jr. (1979). Social Statistics, Revised Second Edition, McGraw-Hill Book Company-New York.

Elmes, D.G., Kantowitz, B.G. & Roediger, H.L. (1985). Research Methods in Psychology, 2nd. Ed., New York: West Publishing Company

SECTION III: RELATIONSHIP BETWEEN COURSE UNIT AND COURSE LEARNING OUTCOMES (CLOs)

(The matrix below shows how the course learning outcomes (CLOs) associates with programme learning outcomes (both KPLOs & SPLOs) and, if exist, the level of quantitative contribution to them.)

Relationship Between CLOs & PLOs

(KPLOs and SPLOs are the abbreviations for Key & Sub- Programme Learning Outcomes, respectively. )
CLOs/PLOs KPLO 1 KPLO 2 KPLO 3 KPLO 4 KPLO 5
1 2 3 4 1 2 3 4 1 2 3 1 2 3 4 1 2 3 4 5 6 7 8 9 10 11 12
CLO1
CLO2
CLO3
CLO4
CLO5

Level of Contribution of the Course to PLOs

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Programme Learning Outcomes Contribution Level (from 1 to 5)
1) Evaluates cognitive, psychological, social reasons and consequences of human behavior. 3
2) Comprehends his/her professional competencies and limitations. 3
3) Reflects his/her knowledge, academic and clinical experience acquired in psychology education in professional practice effectively. 5
4) Applies the theoretical knowledge in business life during a semester. 4
5) Acquires the competencies that develop by the expectations of business world and the society defined as the institutional outcomes of our university on the advanced level in relation with his/her field. 5

SECTION IV: TEACHING-LEARNING & ASSESMENT-EVALUATION METHODS OF THE COURSE

Teaching & Learning Methods of the Course

(All teaching and learning methods used at the university are managed systematically. Upon proposals of the programme units, they are assessed by the relevant academic boards and, if found appropriate, they are included among the university list. Programmes, then, choose the appropriate methods in line with their programme design from this list. Likewise, appropriate methods to be used for the course units can be chosen among those defined for the programme.)
Teaching and Learning Methods defined at the Programme Level
Teaching and Learning Methods Defined for the Course
Lectures
Discussion
Case Study
Problem Solving
Demonstration
Views
Laboratory
Reading
Homework
Project Preparation
Thesis Preparation
Peer Education
Seminar
Technical Visit
Course Conference
Brain Storming
Questions Answers
Individual and Group Work
Role Playing-Animation-Improvisation
Active Participation in Class

Assessment & Evaluation Methods of the Course

(All assessment and evaluation methods used at the university are managed systematically. Upon proposals of the programme units, they are assessed by the relevant academic boards and, if found appropriate, they are included among the university list. Programmes, then, choose the appropriate methods in line with their programme design from this list. Likewise, appropriate methods to be used for the course units can be chosen among those defined for the programme.)
Aassessment and evaluation Methods defined at the Programme Level
Assessment and Evaluation Methods defined for the Course
Midterm
Presentation
Final Exam
Quiz
Report Evaluation
Homework Evaluation
Oral Exam
Thesis Defense
Jury Evaluation
Practice Exam
Evaluation of Implementation Training in the Workplace
Active Participation in Class
Participation in Discussions

Relationship Between CLOs & Teaching-Learning, Assesment-Evaluation Methods of the Course

(The matrix below shows the teaching-learning and assessment-evaluation methods designated for the course unit in relation to the course learning outcomes.)
LEARNING & TEACHING METHODS
COURSE LEARNING OUTCOMES
ASSESMENT & EVALUATION METHODS
CLO1 CLO2 CLO3 CLO4 CLO5
-Lectures -Midterm
-Discussion -Presentation
-Case Study -Final Exam
-Problem Solving -Quiz
-Demonstration -Report Evaluation
-Views -Homework Evaluation
-Laboratory -Oral Exam
-Reading -Thesis Defense
-Homework -Jury Evaluation
-Project Preparation -Practice Exam
-Thesis Preparation -Evaluation of Implementation Training in the Workplace
-Peer Education -Active Participation in Class
-Seminar - Participation in Discussions
-Technical Visit
-Course Conference
-Brain Storming
-Questions Answers
-Individual and Group Work
-Role Playing-Animation-Improvisation
-Active Participation in Class

Contribution of Assesment & Evalution Activities to Final Grade of the Course

Measurement and Evaluation Methods # of practice per semester Level of Contribution
Quizzes 2 % 20.00
Midterms 1 % 30.00
Semester Final Exam 1 % 50.00
Total % 100
PERCENTAGE OF SEMESTER WORK % 50
PERCENTAGE OF FINAL WORK % 50
Total % 100

SECTION V: WORKLOAD & ECTS CREDITS ALLOCATED FOR THE COURSE

WORKLOAD OF TEACHING & LEARNING ACTIVITIES
Teaching & Learning Activities # of Activities per semester Duration (hour) Total Workload
Course 13 3 39
Laboratory 6 2 12
Application 2 2 4
Special Course Internship (Work Placement) 0 0 0
Field Work 0 0 0
Study Hours Out of Class 10 1 10
Presentations / Seminar 0 0 0
Project 0 0 0
Homework Assignments 0 0 0
Total Workload of Teaching & Learning Activities - - 65
WORKLOAD OF ASSESMENT & EVALUATION ACTIVITIES
Assesment & Evaluation Activities # of Activities per semester Duration (hour) Total Workload
Quizzes 1 28 28
Midterms 1 24 24
Semester Final Exam 1 36 36
Total Workload of Assesment & Evaluation Activities - - 88
TOTAL WORKLOAD (Teaching & Learning + Assesment & Evaluation Activities) 153
ECTS CREDITS OF THE COURSE (Total Workload/25.5 h) 6