In addition, Genesis 1:1-2:3; Psalm 104 (a poetic account of creation); Genesis 6-9 (the Flood); and two historical psalms, 105 and 106, were plotted. We determined the coefficients of the equation for the curve that fit this non-linear data by maximizing the logarithm of the odds (P/(1-P)) for the ratios of preterites to finite verbs for the 97 texts .85 for the unweighted, .88 for the weighted—highly effective in reducing the variation.
Preterite verbs (green) clearly dominate in narrative. A perfect classification model would classify all passages into their actual genre. Classification accuracy is indicated by proportional change in error (t The binomial statistic was used to test the null hypothesis that the proportion incorrectly classified by the model is no lower than that of random classification.
Is Genesis 1:1-2:3 a historical narrative (with the plain sense of its words corresponding to reality and the sequence of events portrayed correlating with real time) or is it an extended poetic metaphor?
Answering this vital question has been the focus of my RATE research, the results of which will appear as a chapter in the final RATE book.
Below is just a sample of the exciting results of this study: paired-texts data, control charts, and logistic regression.
Although the Hebrew text's ordinary morphology, syntax, and vocabulary betray no indication that it should be read other than as a narrative, many who hold to an old earth model, read it as mere poetry. I'm convinced the text will tell us whether the author wanted us to read it as poetry or prose: countable linguistic features—which allow statistical analysis—can inform us of what his original readers would have intuitively grasped. 105; 106 In control charts, data points within three standard deviations of the mean have a 99.73 percent probability of belonging to that population; whereas points outside these control limits do not belong.
I chose to study the distribution of Biblical Hebrew finite verbs (verbs inflected for person, gender, and number), to find the answer. The charts showed that the mean of the ratios of preterites to finite verbs for narrative differs from poetry.
A statistically valid, stratified random sample of 48 narrative and 49 poetry texts was generated from all the narrative and poetry texts and then subjected to statistical tests in order to answer two questions: (1) Is the finite verb distribution dependent on genre (poetry versus narrative)? Finite verb distribution, therefore, is dependent on genre.and (2) If it is, can the distribution in a given text be used to determine its genre? Moreover, since Genesis 1:1-2:3 was far outside the upper control limits for poetic texts, it is not part of that population.The paired-texts data plot (figure 1) contrasts the distributions of finite verbs for narrative and poetic versions of the same event: the crossing of the Red Sea (Exodus 14, narrative; Exodus 15:1-19, poetry); Baraq and Deborah defeating the Canaanites (Judges 4, narrative; Judges 5, poetry). Logistic regression is ideal for our data, because a text is either a narrative or poetry, with assigned probabilities (P) of 1 and 0, respectively.Points on the curve are the probability that a text is a narrative for a given ratio of preterites to finite verbs. The Biblical Hebrew Creation Account: New Numbers Tell the Story.Using this curve the probability that Genesis 1:1-2:3 (X The distribution of preterites to finite verbs in Hebrew narrative differs distinctly from that in Hebrew poetry. Moreover, a logistic regression model fitted to the ratio of preterites to finite verbs categorizes texts as narrative or poetry to an extraordinary level of accuracy.