TYPE OF COURSE UNIT	Elective Course
LEVEL OF COURSE UNIT	Master's Degree Without Thesis
YEAR OF STUDY	-
SEMESTER	-
NUMBER OF ECTS CREDITS ALLOCATED	7
NAME OF LECTURER(S)	Instructor Esra Kınay Çiçek
LEARNING OUTCOMES OF THE COURSE UNIT	At the end of this course, the students; 1) interpret statistical concepts 2) make inferences related to different statistical distributions 3) conduct hypothesis testing and interpret the results 4) create data files in SPSS, use data cleaning procedures, and analyze data, 5) choose appropriate statistical analysis for a given research question 6) interpret Type I and Type ıı error rates and interpret effect sizes 7) interpret the central limit theorem 8) distinguish among statistical distributions, 9) test the assumptions of test statistics.
MODE OF DELIVERY	Face to face
PRE-REQUISITES OF THE COURSE	No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT
COURSE DEFINITION	This course focuses on developing the basic concepts in statistics which are necessary to analyze different research questions in education. The course will be conducted by analyzing various data sets by SPSS program and the results of SPSS outputs will be interpreted.
COURSE CONTENTS	WEEK TOPICS 1st Week Basic concepts, population, sample, variable, statistic, parameter, descriptive and inferential statistics etc. 2nd Week Creating data files, cleaning data files and basic statistical analyses. 3rd Week Measures of central tendencies and variability. 4th Week Properties of normal distribution and using the normal distribution for probabilistic interpretations. 5th Week Correlation and regression analyses. 6th Week Central limit theorem and hypothesis testing. 7th Week Hypothesis testing: Testing independent means (z-test) 8th Week Hypothesis testing: Testing dependent and independent means (t and F tests) 9th Week Assumptions of test statistics, effect sizes, controlling Type I and Type II errors. 10th Week Hypothesis testing: Comparing more than two independent means. One way analysis of variance. 11th Week Hypothesis testing: Comparing more than two independent means. Repeated analysis of variance. 12th Week Hypothesis testing: Comparing more than two independent means. Two way analysis of variance. 13th Week Statistical control: Covariance analysis for one way design. 14th Week The differences between parametric and non-parametric tests. 15th Week
RECOMENDED OR REQUIRED READING	Hinkle, D.E.,Wiersma, W., ve Jurs, S.G. (1988) Applied Statistics for the Behavioral Sciences. Boston: Houghton Mifflin Company Arıcı,Hüsnü. (1984) İstatistik Yöntemler ve Uygulamalar. Ankara: Meteksan Matbaacılık
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS	Lecture,Questions/Answers,Practice,Problem Solving,Discussion
ASSESSMENT METHODS AND CRITERIA	Quantity Percentage(%) Mid-term 1 30 Assignment 1 30 Total(%) 60 Contribution of In-term Studies to Overall Grade(%) 60 Contribution of Final Examination to Overall Grade(%) 40 Total(%) 100
ECTS WORKLOAD	Activities Number Hours Workload Midterm exam 1 2 2 Preparation for Quiz Individual or group work 14 4 56 Preparation for Final exam 1 24 24 Course hours 14 1 14 Preparation for Midterm exam 1 20 20 Laboratory (including preparation) 14 2 28 Final exam 1 15 15 Homework 5 4 20 Report writing 5 4 20 Total Workload 199 Total Workload / 30 6,63 ECTS Credits of the Course 7
LANGUAGE OF INSTRUCTION	Turkish
WORK PLACEMENT(S)	No