Factor analysis is a statistical method used to describe variability among observed variables. It is a collection of methods used to examine how underlying constructs influence the responses on a number of measured variables.

There are basically two types of factor analysis: Exploratory and Confirmatory.

- Exploratory factor analysis (EFA) attempts to discover the nature of the constructs influencing a set of responses.
- Confirmatory factor analysis (CFA) tests whether a specified set of constructs is influencing responses in a predicted way.

Factor analyses are performed by examining the pattern of correlations (or covariance’s) between the observed measures. Measures that are highly correlated (either positively or negatively) are likely influenced by the same factors, while those that are relatively uncorrelated are likely influenced by different factors.

**Scree plot**: The Cattell scree test plots the components as the X axis and the corresponding Eigenvalues as the Y-axis. A scree plot shows the sorted eigenvalues, from large to small, as a function of the eigenvalue index.

A Scree Plot is a simple line segment plot that shows the fraction of total variance in the data.

The Scree Plot has two lines: the lower line shows the proportion of variance for each principal component, while the upper line shows the cumulative variance explained by the first N components. The principal components are sorted in decreasing order of variance, so the most important principal component is always listed first.

**Group**: Marketing 5

**Author**: Sanandan Atrey

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