Exploratory Data Analysis
Exploratory data analysis (EDA) is a data-driven conceptual framework for analysis that is based primarily on the philosophical and methodological work of John Tukey and colleagues, which dates back to the early 1960s. Tukey developed EDA in response to psychology's overemphasis on hypodeductive approaches to gaining insight into phenomena, whereby researchers focused almost exclusively on the hypothesis-driven techniques of confirmatory data analysis (CDA). EDA was not developed as a substitute for CDA; rather, its application is intended to satisfy a different stage of the research process. EDA is a bottom-up approach that focuses on the initial exploration of data; a broad range of methods are used to develop a deeper understanding of the data, generate new hypotheses, and identify patterns in the data. In contrast, ...
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Reader's Guide
Descriptive Statistics
Distributions
Graphical Displays of Data
Hypothesis Testing
Important Publications
Inferential Statistics
Item Response Theory
Mathematical Concepts
Measurement Concepts
Organizations
Publishing
Qualitative Research
Reliability of Scores
Research Design Concepts
Research Designs
Research Ethics
Research Process
Research Validity Issues
Sampling
Scaling
Software Applications
Statistical Assumptions
Statistical Concepts
Statistical Procedures
Statistical Tests
Theories, Laws, and Principles
Types of Variables
Validity of Scores
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