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R for Microsoft® Excel Users: Making the Transition for Statistical Analysis by Conrad Carlberg

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6. Principal Components Analysis

With principal components analysis we move beyond the types of statistical analysis that you can design using Excel’s built-in worksheet functions. When it’s a matter of basic descriptive statistics, or inferential tests including t-tests and the analysis of variance and covariance, regression analysis, and logistic regression, you don’t have to look further in Excel than worksheet functions such as AVERAGE( ), DEVSQ( ), LINEST( ), F.DIST.RT( ), and EXP( ) to assemble a complete analysis.

But when it comes to analysis that involves digging out underlying variables that are observed only indirectly, ...

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