Information Package / Course Catalogue
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Theory: 0
Prt.: 0
Credit: 0
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Objectives of the Course

Course Content

Name of Lecturer(s)
Learning Outcomes
1.Students should be able to comprehend the importance of statistics in life and science.
2.Students should be able to get known concepts/terms in statistics.
3.Students should be able to distinguish data and theri types.
4.Students should be able to get known about commonly used statsitics programs and their basic commands.
5.Students should be able to put the data into the computer.
6.Students should be able to comprehend the aims and features of descriptive and inferential statistics.
7.Students should be able to distinguish the features and uses of parametrical and non-parametrical tests.
8.Students should be able to do descriptive statistics on computer and interpret them.
9.Students should be able to apply parametrical tests, put the results into tables and interpret them.
10.Students should be able to apply parametrical tests, put the results into tables and interpret them.
11.Students should be able to apply non-parametrical tests, put the results into tables and interpret them.
12.Students should be able to do correlational and regression analyses and interpret them.
Recommended or Required Reading
1.Akhun, İ. (1988). Temel istatistiksel kavramlar H.Ü. Basılmış Ders Notları (3. Baskı). Ankara.
2.Blalock, M., H. (1972). Social statistics (2nd Ed). New York: McGraw-Hill
3.Book Co., Baykul, Y. (1999). İstatistik metodlar ve uygulamalar (3.Baskı). Ankara: Anı Yayıncılık.
4.Büyüköztürk, Ş. (2010). Sosyal bilimler için veriri analizi el kitabı, Araştırma Deseni SPSS Uygulamaları ve Yorum. Ankara: PegemA yayıncılık.
5.Grimm, L., G. (1993). Statistical application for the behavioral sciences. New York: John Wiley and Sons Inc.
6.Mann, P., S. (1992). Introductory statistics. New York: John Wiley and Sons Inc.
7.Pallat, J. (2001). SPSS Survival manual: A step by step guide to data analysis using SPSS for Windows (Version 10). Buckingham: Open University Pres.
8.Raynald Levesque and SPSS Inc.(2007). Programming and Data Management for SPSS® Statistics 17.0 A Guide for SPSS Statistics and SAS® Users. Chicago: SPSS Inc.
9.Smith, G., M. (1962). A simplified guide to statistics for psychologhy and education. New York: Holt, Rinehart and Education Inc.
10.Vadum, C., A. ve Rankin, O., N. (1998). Psychological research. New York: McGraw-Hill Book Co.
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction of the course: Content, necessity, importance, forming expectations, explaining the process and the criteria of evaluation. A general view to statistics.
Week 2 - Theoretical
Importance of statsitics in life and scientific studies and examples for practise.
Week 3 - Theoretical
Bsic concepts: Statistics, parameter, universe, sample, data gathering instrumentsı, scales and types of tghem, data and types of them, variables and types of them.
Week 4 - Theoretical
Commonly used statistics programs (SPSS, Statistica, minitab, SAS) , general description of them.
Week 5 - Theoretical
Introduction of SPSS data input page and practise of basic commands.
Week 6 - Theoretical
Inputting data in SPSS.
Week 7 - Intermediate Exam
Midterm Exam
Week 8 - Theoretical
Studying the types, aims and features of desricptive and anlam çıkarıcı statistics.
Week 9 - Theoretical
Doing descriptive statistics on SPSS, putting the results into tgables and intgerpreting them.
Week 10 - Theoretical
Parametrical statistics: Testing the differences between two means (t tests for related samples).
Week 11 - Theoretical
Parametrical statistics: Testing the differences between two means (t tests for unrelated samples)
Week 12 - Theoretical
Parametrical statistics: Testing the differences among more than two means (ANOVA for single group and unrelated samples).
Week 13 - Theoretical
Parametrical statistics: Testing the differences among more than two means (complicated- parametrical statistics: ANOVA (for single group) to test the differences among more than two means).
Week 14 - Theoretical
Non-parametrical tests: Chi-square.
Week 15 - Theoretical
Correlational analyses: Correlation and simple linear regression.
Week 16 - Final Exam
Final Exam
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%40
Final Examination1%70
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory142256
Lecture - Practice140228
Laboratory140228
Midterm Examination1527
Final Examination1527
TOTAL WORKLOAD (hours)126
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
PÇ-11
OÇ-1
OÇ-2
4
4
4
4
4
4
4
4
4
4
4
OÇ-3
5
5
5
5
5
5
5
5
5
5
5
OÇ-4
OÇ-5
OÇ-6
OÇ-7
OÇ-8
5
5
5
5
5
5
5
5
5
5
5
OÇ-9
OÇ-10
OÇ-11
OÇ-12
4
4
4
4
4
4
4
4
4
4
4
Adnan Menderes University - Information Package / Course Catalogue
2026