因子(编程语言)
探索性因素分析
探索性分析
计算机科学
数据科学
程序设计语言
机器学习
结构方程建模
作者
An Gie Yong,Sean Pearce
标识
DOI:10.20982/tqmp.09.2.p079
摘要
The following paper discusses exploratory factor analysis and gives an overview of the statistical technique and how it is used in various research designs and applications.A basic outline of how the technique works and its criteria, including its main assumptions are discussed as well as when it should be used.Mathematical theories are explored to enlighten students on how exploratory factor analysis works, an example of how to run an exploratory factor analysis on SPSS is given, and finally a section on how to write up the results is provided.This will allow readers to develop a better understanding of when to employ factor analysis and how to interpret the tables and graphs in the output.The broad purpose of factor analysis is to summarize data so that relationships and patterns can be easily interpreted and understood.It is normally used to regroup variables into a limited set of clusters based on shared variance.Hence, it helps to isolate constructs and concepts.
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