Published 3/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 570.27 MB | Duration: 1h 23m

What you'll learn
Classical test theory
Theory/Math behind Classical test theory
Analysis of data
No programming or math experience needed. Everything will be taught from scratch
Welcome to "Mastering Classical Test Theory with R" – your comprehensive guide to understanding and applying the principles of Classical Test Theory (CTT). In this course, we'll break down the complexities of psychological assessments, debunk common myths surrounding test theory, and equip you with practical skills to analyze and interpret test data with confidence.What You'll Learn:1. Understanding Classical Test Theory (CTT) Made Easy: - Dive into the fundamentals of Classical Test Theory, learning how to conceptualize test scores in terms of true score and error score. - Explore key concepts such as reliability, and item analysis through easy-to-follow explanations and relatable examples. - Demystify the core principles of CTT, making complex theories accessible to learners of all backgrounds.2. Debunking Myths of Classical Test Theory: - Bust common myths surrounding Classical Test Theory, including misconceptions about its complexity and relevance in modern assessment practices. - Discover how CTT remains a foundational framework in psychometrics, with applications spanning from traditional paper-and-pencil tests to online assessments and performance evaluations.3. Analyzing and Interpreting Data Using Free Software and R Language: - Utilize R and a FREE software to analyze test data, calculate reliability coefficients, conduct item analysis.Who Is This Course For:This course is ideal for students, researchers, educators, and practitioners seeking to deepen their understanding of psychological assessments and improve their data analysis skills. Whether you're new to test theory or looking to enhance your proficiency in statistical analysis with R, this course offers something for everyone.
Section 1: Introduction
Lecture 1 Introduction
Section 2: Reliability types and analysis
Lecture 2 Data types
Lecture 3 Types of reliability
Lecture 4 Test retest
Lecture 5 Parallel reliability
Lecture 6 Split half reliability
Lecture 7 Cronbach conceptually
Lecture 8 Item statistics
Lecture 9 Free Software analysis
Lecture 10 Analysis using R
Section 3: Classical test theory
Lecture 11 True score theory
Lecture 12 Cronbach derivation
Psychologists,Data analyst,Psychometricians,Data scientists,Researcher