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Week
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Topics
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Study Metarials
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1
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Description of course content, practices and assessment Multiple Comparison Methods
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R2- Chapter 7-8-9
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2
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Random Block Design, RBD-p
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R1- Chapter 16
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3
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Random Block Design, RBD-p implementation
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R1- Chapter 16
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4
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Completely Random Factorial Design, CRF-pq
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R1- Chapter 16
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5
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Completely Random Factorial Design, CRF-pq implementation
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R1- Chapter 16, R3-Chapter 6
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6
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Covariance Analysis
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R1- Chapter 3
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7
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Covariance Analysis implementation
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R3-Chapter 8
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8
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Multiple Regression-I
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R1- Chapter 6
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9
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Multiple Regression-II
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R1- Chapter 6
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10
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Multiple Regression implementation
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R1- Chapter 6, R3-Chapter 7
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11
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Non-Parametric Statistics: Chi-Square
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R1- Chapter 17, R2-Chapter 10
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12
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Non-Parametric Statistics: Mann-Whitney U Test, Wilcoxon Signed Rank Test, Kruskal-Wallis Test and its implementation-I
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R1- Chapter 18, R2-Chapter 11-12-13, R3- Chapter 10
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13
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Non-Parametric Statistics: Mann-Whitney U Test, Wilcoxon Signed Rank Test, Kruskal-Wallis Test and its implementation-II
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R1- Chapter 18, R2-Chapter 11-12-13, R3- Chapter 10
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14
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Project presentations
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R1- Chapter 1-18, R2-Chapter 1-13, R3- Chapter 1-10
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Prerequisites
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-
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Language of Instruction
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Turkish
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Responsible
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Assoc. Prof. Dr. Özlem Yeşim Özbek
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Instructors
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-
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Assistants
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-
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Resources
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R1. Kirk, R. E. (2008). Statistics an Introduction. Thomson Wadsworth.
R2. Büyüköztürk, Ş., Çokluk, Ö., & Köklü, N. (2013). Sosyal Bilimler İçin İstatistik. PegemA Yayıncılık.
R3. Büyüköztürk, Ş. (2018). Sosyal Bilimler İçin Veri Analizi El Kitabı: İstatistik. Araştırma Deseni, SPSS Uygulamaları ve Yorum. PegemA Yayıncılık.
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Supplementary Book
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SR1. Tan, Ş. (2016). SPSS ve Excel Uygulamalı Temel İstatistik 1. PegemA Yayıncılık.
SR2. Field, A. (2009). Discovering statistics using SPSS. Sage publications.
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Goals
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It is aimed that students will be able to comprehend the types of statistics suitable for analyzes involving two or more variables, and to choose appropriate statistical methods for the given problems and interpret the results..
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Content
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Multiple comparison tests, Random block design ANOVA, Factorial ANOVA, Analysis of Covariance, Multiple regression analysis and non-parametric statistical analysis methods.
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Program Learning Outcomes |
Level of Contribution |
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1
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Reviews and evaluates national and international literature about interested field.
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3
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2
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Develops research proposal based on literature review.
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-
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3
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Presents and discusses research report.
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3
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4
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Acquires the information regarding the test theories to develop measurement instrument.
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-
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5
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Acquires the knowledge of the methods and techniques of scientific researches.
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2
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6
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Acquires the knowledge of the softwares used to analyse quantitative reserach data.
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-
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7
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Distinguishes the similarities and differences of terms special to measurement and evaluation area.
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-
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8
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Establishes a relationship between psychometric testing qualifications and the testing theorems which are the basis to develop measurement materials.
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-
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9
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Picks the appropriate measurement materials according to the psychometric characteristics.
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-
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10
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Interprets software outputs used to analyze quantitative research data.
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-
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11
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Evaluates the results of the national and international exams.
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-
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12
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Has the fundamental knowledge of concepts related to measurement and evaluation, statistics and research methods.
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4
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13
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Interprets and critiques the recent developments related to measurement and evaluation.
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-
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14
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Carries out a research related to measurement and evaluation.
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-
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15
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Provides a technical support for a solution of the problems faced by the other areas of social sciences.
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-
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