Psychometrics-Classical Test Theory (Simplified Mathematics)

Psychometrics-CTT

What you'll learn

Psychometrics

Classical test theory

Theory/Math behind Classical test theory

Analysis of data

Requirements

No programming or math experience needed. Everything will be taught from scratch

Description

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.

Overview

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