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Course Description Course Name : Applied Educational Statistics I Course Code : PDR 705 Course Type : Optional Level of Course : Second Cycle Year of Study : 1 Course Semester : Fall and Spring (16 Weeks) ECTS : 6 Name of Lecturer(s) : Asst.Prof.Dr. SABAHATTİN ÇAM Learning Outcomes of the Course : Defines descriptive statistics Explains what statistical assumption is Explains the relation between measurement and statistical inference Accesses data to SPSS program of a data set Tests the difference of range between frequencies in a data set Knows the relations between variables in a data set Analyzes means obtained from the data set via T test Compares the different grades of groups in a descriptive research via ANOVA technique Applies ANOVA technique to the data obtained from experimental research Applies the relevant ANCOVA to descriptive and experimental studies Compares the grades of different groups in data sets which don´t have normal distributions using the appropriate statistical technique Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : The main purpose of this course is to enable the students to gain knowledge, skills and attitudes regarding scientific research techniques. Course Contents : The course includes the basic statistical concepts and parametric and nonparametric techniques used in social sciences. 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 of course content, studies in the course, methods, techniques and evaluation Examining relevant sources Question-answer and discussion 2 Statistics, the importance of stastistics in scientific research Examining relevant sources Question-answer and discussion 3 Measurement , variance and the types of variance, the types of statistical techniques Examining relevant sources Question-answer and discussion 4 Statistical assumption and its errors Criterion for the determination of statistical tecchnique in data analysis Examining relevant sources Question-answer and discussion 5 Accessing data to SPSS program Examining relevant sources Question-answer and discussion 6 Calculation of descriptive statistics with SPSS program in a data set Examining relevant sources Question-answer and discussion 7 Techniques in data set to calculate relation Examining relevant sources Question-answer and discussion 8 Midterm Exam writting questions writting questions 9 The use of t test in data analysis Examining relevant sources Question-answer and discussion 10 The use of T test in data analysis Examining relevant sources Question-answer and discussion 11 Using ANOVA technique in descriptive researches Examining relevant sources Question-answer and discussion 12 Using ANOVA in experimental studies Examining relevant sources Question-answer and discussion 13 Covariance analysis technique Examining relevant sources Question-answer and discussion 14 Other non-parametric analysis techniques Examining relevant sources Question-answer and discussion 15 General evaluation of the course Examining relevant sources Question-answer and discussion 16/17 Final exam writting questions writting questions   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  Baykul, Y. (1997). İstatistik: Metodlar ve Uygulamalar (2. baskı). Ankara: Anı Yayıncılık  Büyüköztürk, Ş. (2002). Sosyal Bilimler İçin veri Analizi El Kitabı. Ankara: PegemA Yayıncılık.  Hovardaoğlu, S. (1994). Davranış Bilimleri İçin İstatistik. Ankara: Hatipoğlu Yayınları. 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 12 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. 5 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. 3 5 Uses and develops individual assessment techniques. 5 6 Guides the graduates of the field of educational sciencies within the framework of the knowledge and experiences that specialized training provides. 3 7 Gains knowledge and experience about the appliations which can make the field of expertise functional in educational field. 5 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. 4 10 Integrates the theoretical knowledge within the scope of the field of educational sciences with the field of application. 2 11 Takes responsibility for solving the problems at the local and national level during the educational science-oriented applications. 3 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. 0 14 Informs his/her colleagues about the processes regarding the field of expertise and conclusions reached. 5 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. 5 18 Identifies the sources of the problems in the field of educational sciences and contributes to the solution of these problems. 4 19 Provides the cooperation of all partners in educational environment stating the necessity of the field of expertise. 3 20 Assesses the necessities which reveal through the applications related to the field of expertise in a critical way. 2 * 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) 13 3 39     Out of Class Study (Preliminary Work, Practice) 13 3 39 Assesment Related Works     Homeworks, Projects, Others 12 4 48     Mid-term Exams (Written, Oral, etc.) 1 10 10     Final Exam 1 20 20 Total Workload: 156 Total Workload / 25 (h): 6.24 ECTS Credit: 6