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Factor Analysis

In: Statistical Methods in Social Science Research

Author

Listed:
  • S. P. Mukherjee

    (University of Calcutta, Department of Statistics)

  • Bikas K. Sinha

    (Indian Statistical Institute)

  • Asis Kumar Chattopadhyay

    (University of Calcutta, Department of Statistics)

Abstract

Factor Analysis is a method for modeling observed variables and their covariance structure, in terms of a smaller number of underlying unobservable factors. The factors are considered as broad concepts or ideas that may describe an observed phenomenon. Factor analysis may be considered to be a generalization of principal component method since here also we replace the large number of variables by a smaller number of unknown factors. However, the aim of principal component analysis is to explain the variance while factor analysis explains the covariance among the variables. Hence, factor analysis is a way to understand how the patterns of relationship between several variables are caused by a smaller number of latent variables, according to their common aspects. These hidden variables are called factors.

Suggested Citation

  • S. P. Mukherjee & Bikas K. Sinha & Asis Kumar Chattopadhyay, 2018. "Factor Analysis," Springer Books, in: Statistical Methods in Social Science Research, chapter 0, pages 103-111, Springer.
    • Handle: RePEc:spr:sprchp:978-981-13-2146-7_10
    DOI: 10.1007/978-981-13-2146-7_10
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