Data Mining
Modern researchers in various fields are confronted by an unprecedented wealth and complexity of data. However, the results available to these researchers through traditional data analysis techniques provide only limited solutions to complex situations. The approach to the huge demand for the analysis and interpretation of these complex data is managed under the name of data mining, or knowledge discovery. Data mining is defined as the process of extracting useful information from large data sets through the use of any relevant data analysis techniques developed to help people make better decisions. These data mining techniques themselves are defined and categorized according to their underlying statistical theories and computing algorithms. This entry discusses these various data mining methods and their applications.
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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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