Course Information


Course Information
Course Title Code Semester L+U Hour Credits ECTS
STATISTICS IN BEHAVIORAL SCIENCES I 600306711130 3 + 0 3.0 8.0

Prerequisites None

Language of Instruction Turkish
Course Level Graduate Degree
Course Type Compulsory
Mode of delivery
Course Coordinator
Instructors Seher YALÇIN
Assistants
Goals Making and interpreting statistical analyzes with the SPSS program by gaining basic and inferential statistical information
Course Content Basic concepts, Descriptive statistics, Distributions, Standard scores, Correlation, Regression, Data Analysis with SPSS (Comparison of the averages, Regression analysis, Chi-square, Non-parametric tests)
Learning Outcomes 1) Know basic concepts about statistics.
2) Tests the assumptions of basic statistical techniques.
3) Applies the basic statistical techniques on a sample dataset.
4) Determines the appropriate statistical technique for a given problem situation.
5) Reports the analysis output in accordance with its standards.

Weekly Topics (Content)
Week Topics Teaching and Learning Methods and Techniques Study Materials
t testing Lecture

 Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
1. Week Basic Concepts Lecture; Question Answer

 Presentation (Including Preparation Time)
2. Week Central Tendency and Distribution Statistics Lecture; Question Answer

 Presentation (Including Preparation Time)
3. Week Central Tendency and Distribution Statistics Lecture; Question Answer

 Presentation (Including Preparation Time)
4. Week Hypothesis Lecture; Question Answer

 Presentation (Including Preparation Time)
5. Week Correlation and correlation types Lecture; Question Answer

 Presentation (Including Preparation Time)
6. Week Regression Lecture; Question Answer

 Homework
7. Week Midterm exam Question Answer

 Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
8. Week Start to SPSS Lecture; Question Answer

 Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
10. Week Analysis of Variance (ANOVA) Lecture; Question Answer

 Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
11. Week Chi-Square Analysis Lecture; Question Answer

 Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
12. Week Regression Lecture; Question Answer

 Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
13. Week Factor Analysis Lecture; Question Answer

 Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)
14. Week Factor Analysis Lecture; Question Answer

 Practice (Teaching Practice, Music/Musical Instrument Practice, Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice)

Sources Used in This Course
Recommended Sources
Baykul, Y. ve Güzeller, C. O. (2014). Sosyal bilimler için istatistik SPSS Uygulamalı. Ankara: Pegem Akademi
Büyüköztürk, Ş. (2012). Sosyal bilimler için veri analizi elkitabı. Ankara: Pegem Akademi

ECTS credits and course workload
Event Quantity Duration (Hour) Total Workload (Hour)
Course Duration (Total weeks*Hours per week) 14 3
Work Hour outside Classroom (Preparation, strengthening) 14 3
Homework 12 3
Report (Including Preparation and presentation Time) 3 15
Practice (Teaching Practice, Music/Musical Instrument Practice , Statistics, Laboratory, Field Work, Clinic and Polyclinic Practice) 10 3
Midterm Exam 1 1
Time to prepare for Midterm Exam 1 15
Final Exam 1 1
Time to prepare for Final Exam 1 20
Total Workload
Total Workload / 30 (s)
ECTS Credit of the Course
Quick Access Hızlı Erişim Genişlet
Course Information
  • Course Information
  • Weekly Topics (Content)
  • Sources Used in This Course
  • ECTS credits and course workload