PSİ502


Course Title Course Code Program Level
Statistical Packages for Social Sciences (SPSS) and Applications PSİ502 Psikoloji (Tezsiz) M.A / M.Sc.

Course Term
(Course Semester)
Teaching and Learning Methods
Credits
Theory Practice Lab Projects/Field Work Seminars/Workshops Other Total Credits ECTS Credits
02
(Spring)
42 30 120 192 3 7

Teaching Staff Öğr.Gör.Dr.Yusuf KASAP
Language of Instruction Türkçe (Turkish)
Type Of Course Compulsory
Prerequisites No prerequisites
Recommended Optional Programme Component
Course Objectives The aim of the course is to learn basic statistical concepts and methods, to analyse data applying this methods with SPSS and to make statistical inference.
Course Content The content of this course are basic statistical concepts, menus in SPSS, data entry and design, descriptive statistics, parametric and non-parametric tests, regression analysis, correlation analysis.
Learning Outcomes (LO) The students who attended the course and were successful at the end of semester will acquire the followings; 1. Comprehending the basic statistical concepts and definitions, 2. Making data entry and editing to SPSS, 3. Summarizing data which results of scientific research with tables and graphs, 4. Selecting the appropriate statistical analysis according to measurement level, 5. Making statistical analysis with SPSS 6. Interpreting and evaluating outcomes statistically.
Mode of Delivery Face to face
Course Outline
Week Topics
1. Week Introduction of the course
2. Week Basic statistical concepts, types of data, measurement levels
3. Week Menus in SPSS, data entry and data design, change (recode, compute etc.)
4. Week Descriptive statistics, frequency tables
5. Week Graphs, crosstabs
6. Week Normality test and evaluations of assumptions
7. Week Parametric tests of hypotheses (one sample, two samples)
8. Week Parametric tests of hypotheses (more than two samples)
9. Week Non-Parametric tests of hypotheses (the chi-square test of independence, one sample, two samples)
10. Week Non-Parametric tests of hypotheses (more than two samples)
11. Week Simple linear regression
12. Week Multiple regression
13. Week Analysis of correlation
14. Week Applications
Assessment
  Percentage(%)
Mid-term (%) 30
Quizes (%)
Homeworks/Term papers (%)
Practice (%)
Labs (%)
Projects/Field Work (%) 10
Seminars/Workshops (%)
Final (%) 60
Other (%)
Total(%) 100
Course Book (s) and/or References • Akgül, A. (2003). Tıbbı araştırmalarda istatistiksel analiz teknikleri, SPSS uygulamaları. • Joaquim P. Marques de Sá, (2007), Applied Statistics Using SPSS, STATISTICA, MATLAB and R, Springer • Gamgam, H., ALTUNKAYNAK, B., (2008), Parametrik Olmayan Yöntemler-SPSS Uygulamalı, Gazi Kitabevi • Landau, S. And Everit, B.S., (2004), A Handbook of Statistical Analysis Using SPSS,Chapman&Hall/CRC. • Özdamar, K., (1999), Paket Programlar ile İstatistiksel Veri Analizi, Çok Değişkenli Analizler, Kaan Kitabevi. • Runyon, R.P., Coleman, K.A., Pittenger. D.j., (2000), Fundementals of Behavioral Statistics, 9th Edition, McGraw Hill.
Work Placement(s)
The Relationship between Program Qualifications (PQ) and Course Learning Outcomes (LO)

 

 

PQ1

PQ2

PQ3

PQ4

PQ5

PQ6

PQ7

PQ8

PQ9

PQ10

LO1

 

 

 

 

 

4

2

 

 

3

LO2

 

 

 

 

 

 

 

 

 

3

LO3

 

 

 

4

 

4

 

 

 

4

LO4

 

 

 

 

 

 

 

 

4

5

LO5

 

 

 

 

4

 

 

 

 

5

LO6

 

5

4

 

4

5

 

4

 

5

 

* Degree of Contribution: 1 Very Low 2 Low 3 Medium 4 High 5 Very High