The Synoptic Problem and Statistics / Edition 1

The Synoptic Problem and Statistics / Edition 1

by Andris Abakuks
ISBN-10:
1138374784
ISBN-13:
9781138374782
Pub. Date:
09/18/2018
Publisher:
CRC Press
ISBN-10:
1138374784
ISBN-13:
9781138374782
Pub. Date:
09/18/2018
Publisher:
CRC Press
The Synoptic Problem and Statistics / Edition 1

The Synoptic Problem and Statistics / Edition 1

by Andris Abakuks
$77.99 Current price is , Original price is $77.99. You
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Overview

See How to Use Statistics for New Testament Interpretation

The Synoptic Problem and Statistics lays the foundations for a new area of interdisciplinary research that uses statistical techniques to investigate the synoptic problem in New Testament studies, which concerns the relationships between the Gospels of Matthew, Mark, and Luke. There are potential applications of the techniques to study other sets of similar documents.

Explore Hidden Markov Models for Textual Data

The book provides an introductory account of the synoptic problem and relevant theories, literature, and research at a level suitable for academic and professional statisticians. For those with no special interest in biblical studies or textual analysis, the book presents core statistical material on the use of hidden Markov models to analyze binary time series. Biblical scholars interested in the synoptic problem or in the use of statistical methods for textual analysis can omit the more technical/mathematical aspects of the book. The binary time series data sets and R code used are available on the author’s website.


Product Details

ISBN-13: 9781138374782
Publisher: CRC Press
Publication date: 09/18/2018
Pages: 215
Product dimensions: 6.12(w) x 9.19(h) x (d)

About the Author

Andris Abakuks is a lecturer in statistics at Birkbeck, University of London. His research focuses on the application of probability and statistics to problems in theology and New Testament studies.

Table of Contents

Introduction to the Gospel Texts and the Synoptic Problem. The Triple-Link Model. Matthew's and Luke's Use of Mark: A Logistic Regression Approach. Hidden Markov Models for Binary Time Series. Matthew's and Luke's Use of Mark: Hidden Markov Models. Mark’s and Luke’s Use of Matthew. Examples of Synoptic Parallels. Final Conclusions. Appendix. Bibliography. Index.

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