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Course Description Course Name : Applied Educational Statistics I Course Code : EPÖ 705 Course Type : Compulsory Level of Course : Second Cycle Year of Study : 1 Course Semester : Fall (16 Weeks) ECTS : 6 Name of Lecturer(s) : Assoc.Prof.Dr. AHMET DOĞANAY Learning Outcomes of the Course : Explains the basic concepts related to educational statistics Comprehends the place and importance of statistics in the research process Explains the difference between qualitative and quantitative research Recognizes the fundamental statistical techniques used in educational studies Determines the suitable statistical techniques for the research problems Computerizes the data. Makes intended statistical analysis from the processed data Presents the statistical analysis results with graphs or tables in line with research objectives Makes commenst on the statistical analysis results Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : The course aims to improve statistical literacy and provide the students who will use statistics in their research with the ability to interpret statistical data in their research. Course Contents : The course contains basic concepts of statistics applied to education and application of parametric and nonparametric techniques which are used in social sciences. These techniques are taught by using SPSS statistical program. Language of Instruction : Turkish Work Place : Classroom   Course Outline /Schedule (Weekly) Planned Learning Activities Week Subject Student's Preliminary Work Learning Activities and Teaching Methods 1 Introduction and Presentation of the lesson Analyzing different samples by examining related sources Expository teaching, discussion 2 Basic Concepts Place of statistics in the research process Variable, measurement, scale, data and statistical concepts Analyzing different samples by examining related sources Expository teaching, discussion 3 Introduction to SPSS Creation of data file in SPSS Analyzing different samples by examining related sources Expository teaching, discussion 4 Descriptive statistics Frequency distribution Calculation and presentation of frequency distribution in table Calculation of the frequency distribution with graph Analyzing different samples by examining related sources Homework 1 Expository teaching, discussion 5 Measures of central tendency and variability Measures of central tendency Mean Median Mode Variability measures Analyzing different samples by examining related sources Homework 2 Expository teaching, discussion 6 Procedural statistics Universe estimation of the value Normal distribution curve Hypothesis testing Submission of homework Analyzing different samples by examining related sources Expository teaching, discussion 7 Analysis of the differences T Test Independent Samples T Test Analyzing different samples by examining related sources Homework 3 Expository teaching, discussion 8 Midterm exam and submission of homework Preparation for the exam Written exam 9 Paired Samples T Test Analyzing different samples by examining related sources Homework 4 Expository teaching, discussion 10 Analysis of Variance One Way Anova Submission of homework Analyzing different samples by examining related sources Homework 5 Expository teaching, discussion 11 Analysis of variance for repeated measures submission of homework Analyzing different samples by examining related sources Homework 6 Expository teaching, discussion 12 Analysis of covariance Analyzing different samples by examining related sources Homework 7 Expository teaching, discussion 13 Analysis of covariance and submission of homework Analyzing different samples by examining related sources Expository teaching, discussion 14 Chi-Square and submission of homework Analyzing different samples by examining related sources Homework 8 Expository teaching, discussion 15 Analysis of relationships and submission of homework Analyzing different samples by examining related sources Homework 9 Expository teaching, discussion 16/17 Final exam and submission of homework Preparation for the final exam Written exam   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  Baykul, Y. (1996). İstatistik: Metodlar ve uygulamalar. Ankara: Lazer Ofset  Büyüköztürk, Ş. (2002). Sosyal bilimler için veri analizi el kitabı: İstatistik, araştırma deseni SPSS uygulamaları ve yorum. Ankara: PegemA Yayıncılık.  Durmuş, B.; Yurtkoru, E.S. & Çinko, M. (2011). Sosyal bilimlerde SPSS’le veri analizi. Dördüncü baskı. İstanbul: Beta  Kalaycı, Ş. (Edit.). (2008). SPSS uygulamalı çok değişkenli istatistik teknikleri. Ankara: Asil Yayın Dağıtım Ltd. Şti.  Kinnear, P. R. & Gray, C. D. (2000). SPSS for Windows made simple. Release 10. East Sussex: UK. Psychology Pres Ltd. Publishers.  Köklü, N.; Büyüköztürk, Ş. & Bökeoğlu, Ö.Ç. (2007). Sosyal bilimler için istatistik. İkinci baskı. Ankara: PegemA Yayıncılık.  Özdamar, K. (2004). Paket programlar ile istatistiksel veri analizi I. Eskişehir: Kaan Kitabevi.  Özdamar, K. (2004). Paket programlar ile istatistiksel veri analizi II: Çok değişkenli analizler. Eskişehir: Kaan Kitabevi.  Williams, F. (1992). Reasoning with statistics: How to read quantitative research. Fort Worth Philadelphia: Harcaurt Brace Javanovich College Publishers Required Course Material(s)   Assessment Methods and Assessment Criteria Semester/Year Assessments Number Contribution Percentage     Mid-term Exams (Written, Oral, etc.) 1 50     Homeworks/Projects/Others 9 50 Total 100 Rate of Semester/Year Assessments to Success 40   Final Assessments 100 Rate of Final Assessments to Success 60 Total 100   Contribution of the Course to Key Learning Outcomes # Key Learning Outcome Contribution* 1 On the basis of the Educational Sciences BA degree qualificatons, improves his/her knowledge in the same field at the level of expertise. 2 2 Understands the multi-dimensional causes of a problem and evaluates the problem as a whole 2 3 Analyzes a scientific article in the field of educational sciences. 5 4 Uses the theoretical and practical knowledge s/he gained at the level of expertise in the field of educational sciences. 5 5 Uses and develops individual assessment techniques. 4 6 Guides the graduates of the field of educational sciencies within the framework of the knowledge and experiences that specialized training provides. 1 7 Gains knowledge and experience about the appliations which can make the field of expertise functional in educational field. 4 8 Makes prediction about the partner behaviors through the applications concerning the field of expertise. 1 9 Solves a problem in the context of educational sciences in a scientific perspective. 1 10 Integrates the theoretical knowledge within the scope of the field of educational sciences with the field of application. 5 11 Takes responsibility for solving the problems at the local and national level during the educational science-oriented applications. 1 12 Communicates effectively and properly with students, teachers, school administrators, and members of families and working group. 1 13 Has a good command of foreign language to be able to follow the foreign resources related to the field. 2 14 Informs his/her colleagues about the processes regarding the field of expertise and conclusions reached. 3 15 Uses the different statistical techniques and information and communication technologies that s/he needs in the field of expertise. 5 16 Provides the support of the institution employees to make the applications concerning educational sciences successful. 1 17 Develops internalized knowledge in the field of expertise and the related disciplines at the level of expertise. 3 18 Identifies the sources of the problems in the field of educational sciences and contributes to the solution of these problems. 3 19 Provides the cooperation of all partners in educational environment stating the necessity of the field of expertise. 1 20 Assesses the necessities which reveal through the applications related to the field of expertise in a critical way. 3 * Contribution levels are between 0 (not) and 5 (maximum).   Student Workload - ECTS Works Number Time (Hour) Total Workload (Hour) Course Related Works     Class Time (Exam weeks are excluded) 14 3 42     Out of Class Study (Preliminary Work, Practice) 14 4 56 Assesment Related Works     Homeworks, Projects, Others 9 4 36     Mid-term Exams (Written, Oral, etc.) 1 10 10     Final Exam 1 10 10 Total Workload: 154 Total Workload / 25 (h): 6.16 ECTS Credit: 6