BAYBURT University Information Package / Course Catalogue

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Description of Individual Course Units
Course Unit CodeCourse Unit TitleType of Course UnitYear of StudySemesterNumber of ECTS Credits
SIE105Quantitative Data Analysis with SPSS and Lisrel ApplicationsElective116
Level of Course Unit
Second Cycle
Objectives of the Course
The course aims to provide graduate students with the basic concepts, knowledge and skills related to statistical applications in the field of Social Sciences. It is aimed to provide students with both the theoretical knowledge of statistical techniques, which are frequently used in Social Sciences, and the skills of application and interpretation through exemplary research situations.
Name of Lecturer(s)
Doç. Dr. İsmail SARİKAYA
Learning Outcomes
1Understanding and applying statistical techniques used in quantitative data analysis
2To be able to comprehend and interpret analyzes in published research
3Performing analyzes through package programs,
4Arranging the analysis results with the help of tables and figures in accordance with the rules
5Reporting analysis results
Mode of Delivery
Normal Education
Prerequisites and co-requisities
None
Recommended Optional Programme Components
none
Course Contents
Basic data analysis concepts Introduction, installation and menus of SPSS and LISREL applications Normality assumptions and testing, reporting and interpretation via SPSS T-tests for independent groups and repeated measurements, their application, reporting and interpretation One-factor ANOVA and Repeated Measures ANOVA analyses, application, reporting and interpretation Factorial ANOVA analysis, application, reporting and interpretation ANOVA analysis, application, reporting and interpretation for mixed designs Correlation analysis, types, application, reporting and interpretation Simple linear regression analysis, implementation, reporting and interpretation Non-parametric tests, their application, reporting and interpretation Exploratory factor analysis, application, reporting and interpretation with SPSS Confirmatory factor analysis, application, reporting and interpretation with LISREL
Weekly Detailed Course Contents
WeekTheoreticalPracticeLaboratory
1The purpose, importance, content, presentation of the course and general principles regarding the conduct of the course
2Introduction to statistics, basic concepts, installation of SPSS and LISREL packages, variables, measurements, scalesReadings: Additional reading, discussion and study of source books
3Data entry and preparation of data for analysis, description of data, normality and normality assumptionsReadings: Additional reading, discussion and study of source books
4Normal distribution and examination of normal distribution assumption in SPSS, descriptive data analysisReadings: Additional reading, discussion and study of source books
5Parametric tests and their assumptions in SPSSReadings: Additional reading, discussion and study of source books
6SPSS applications with correlation and linear regression analysisReadings: Additional reading, discussion and study of source books
7t-test for independent groups and t-test for repeated measures analyzes and SPSS applicationsReadings: Additional reading, discussion and study of source books
8Midterm exam
9One Way ANOVA, Two Way ANOVA and SPSS applicationsReadings: Additional reading, discussion and study of source books
10Repeated Measures ANOVA and SPSS applicationsReadings: Additional reading, discussion and study of source books
11Mixed ANOVA and SPSS applicationsReadings: Additional reading, discussion and study of source books
12Multivariate ANOVA and SPSS applicationsReadings: Additional reading, discussion and study of source books
13Exploratory Factor Analysis and SPSS applicationsReadings: Additional reading, discussion and study of source books
14Confirmatory Factor Analysis and LISREL applicationsReadings: Additional reading, discussion and study of source books
15Non-parametric tests and SPSS applicationsReadings: Additional reading, discussion and study of source books
16Final Exam
Recommended or Required Reading
• Hulsizer, M.R. & Woolf, L.M. (2009). A guide to teaching statistics: Innovations and best practices. West Sussex: Wiley-Blackwell. • Kalaycı, Ş. (Edt.) (2006). SPSS uygulamalı çok değişkenli istatistik teknikleri (2. Baskı). Ankara: Asil Yayın Dağıtım. • McMillan, J., & Schumacher, S. (2010). Research in education: Evidence-based inquiry (7th edition). Boston: Pearson. • Muijs, D. (2004). Doing quantitative research in education with SPSS. London: Sage. • Sipahi, B., Yurtkoru, E.S., & Çinko, M. (2008). Sosyal bilimlerde SPSS’le veri analizi (2. Baskı). İstanbul: Beta. • Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed). Boston: Allyn and Bacon. Ders kapsamında okutulması ve tartışılması planlanan tez, makale ve sunum gibi etkinlikler ilgili hafta içerisinde paylaşılacaktır. Kaynak seçiminde güncelliğin esas alınmasından dolayı ek kaynaklar değişebilmektedir.
Planned Learning Activities and Teaching Methods
Assessment Methods and Criteria
Term (or Year) Learning ActivitiesQuantityWeight
Midterm Examination1100
SUM100
End Of Term (or Year) Learning ActivitiesQuantityWeight
Final Examination1100
SUM100
Term (or Year) Learning Activities30
End Of Term (or Year) Learning Activities70
SUM100
Language of Instruction
Turkish
Work Placement(s)
none
Workload Calculation
ActivitiesNumberTime (hours)Total Work Load (hours)
Midterm Examination111
Final Examination122
Attending Lectures14342
Practice3618
Report Presentation236
Individual Study for Mid term Examination6318
Individual Study for Final Examination9654
Reading12224
Performance7214
TOTAL WORKLOAD (hours)179
Contribution of Learning Outcomes to Programme Outcomes
LO1
LO2
LO3
LO4
LO5
* Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High