from all variants

discussed in the textual commentary TCG

Wieland Willker, 2009

Principal Component Analysis (PCA) is a multivariate analysis technique which finds major patterns in data variability. In mathematical terms, it is finding eigenvalues and corresponding eigenvectors (=principal components, PC). Most important are the first few principal components that explain most of the observed variance; the rest of them are mostly random fluctuations. Thus, by plotting data versus first 2 or 3 PC we can reduce dimensionality of the data without much loss of information.

Other analyses I have done:

- Principal Component Analysis of John 1-5 (from R. Swanson, complete collations)

- Principal Component Analysis of John 1-10 (from the Text&Textwert collations, Muenster)

Gospel of Matthew:

Gospel of Mark:

Gospel of Luke:

Gospel of John: