Abstract
This chapter discusses how to express huge data and measured variables by a small number of equations called factors to describe the relationship between the original variables. The number of factors should be less than of the original variables. This analysis is called factor analysis, which is a multivariate technique used as a data reduction. Factor analysis produces a wonderful result if the original variables are highly correlated. The variables associated with each factor are highly correlated among themselves and have a very weak relationship with other factors. A step-by-step procedure is given to present factor analysis with detailed explanation. The procedure is supported by real case studies obtained from environmental science to illustrate the steps of the analysis, including the extraction of different factors, selecting the required factors, and the interpretation of the R outputs. Finally, the chapter will guide the reader on how to extract smart conclusions. The built-in functions and codes for factor analysis are provided with the structure and explanation for each step.
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