This graph depicts which doctrines are more concentrated in which books of scripture. To learn more about the data and methods used to generate this graph, visit Textual analysis of Book of Mormon timeline proves it could not have been faked.
For each axis, beyond being able to choose any of the specific books of scripture, one can also select the principal components of these books. Principal components are made up datapoints that broadly summarize all the data. Since in this graph, the principal components are the actual books of scripture, the principal components are more confusing, but it appears that the first principal component differentiates New Testament books from Old Testament books – which it does by comparing the distribution of ideas between each book. And to note, when the principal components are calculated, the algorithm doesn’t know what volume each individual book is from, so its results purely arise from the correlations it finds in distribution of doctrines it measures across the books of scripture, where each book has its own distribution. Principal components work sequentially – so once the first principal component is computed, the next principal component is designed to explain all of the parts of the data not explained by the first principal component – meaning that each principal component measures a different thing from the previous ones, and the first few principal components will be much more important than the last ones.
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