--- In

gthomas@yahoogroups.com, "rj.godijn" <rj.godijn@...> wrote:

>

> a Mark/Q overlap means that Q theorists assume

> that the logion is found in both Q and Mark.

Hi Richard,

Of course that is consistent with the view that both Mark and Q derive

from Thomas. Maybe I should call this the Five Source Theory!

> I am not aware of any current Q econstruction that

> does not include the parable of the mustard seed...

> I think sticking to the schemas of Patterson and Mack

> means that you include GTh 20, because Patterson

> considers it a GTh/Q twin, but made a mistake in not

> including it as a Q parallel in his list (the same

> goes for GTh 94).

I agree. I will revise the file I uploaded to include GTh 20 and GTh

94. The revised Pearson correlation for Q1a has p <= 0.00444, and for

Q1b p <= 0.148. This would leave the regression for Q1a significant at

the 99% confidence interval, but that for Q1b not significant at the

95% confidence interval.

Unless, that is, a new series (Q1c) begins following GTh 96.

This would produce the following sequence:

GTh26 = QC1.01 = QS12 = Q1a

GTh34 = QC1.01 = QS11 = Q1a

GTh45 = QC1.01 = QS13 = Q1a

GTh54 = QC1.01 = QS8 = Q1a

GTh68 = QC1.01 = QS8 = Q1a

GTh69 = QC1.01 = QS8 = Q1a

GTh73 = QC1.02 = QS20 = Q1a

GTh86 = QC1.02 = QS19 = Q1a

GTh92 = QC1.03 = QS27 = Q1a

GTh94 = QC1.03 = QS27 = Q1a

GTh21 = QC1.03 = QS27 = Q1b

GTh33 = QC1.04 = QS35 = Q1b

GTh51 = QC1.04 = QS35 = Q1b

GTh61 = QC1.04 = QS35 = Q1b

GTh76 = QC1.05 = QS40 = Q1b

GTh96 = QC1.06 = QS46 = Q1b

GTh20 = QC1.06 = QS46 = Q1c

GTh55 = QC1.07 = QS52 = Q1c

GTh101 = QC1.07 = QS52 = Q1c

Here for each set - Q1a, Q1b and Q1c - an increase in GTh Saying Number

is associated with increase or sameness of Q1 Cluster Number.

Obviously there is a question of forcing linear sequences by starting

over when it is convenient to do so. This involves starting over twice

out of 18 opportunities. If this can be described by a binomial

distribution, then P <= 0.001 (0-2 successes, 18 trials,

TrialP(success) = 0.5. However this I think this underestimates P, as

for most data pairs (GTh, QC) the probability is greater than 0.5 that

another data pair has greater than or same Q Cluster Number. If the

effective TrialP(success) >= 0.31, then P <= 0.05. I will have to see

if I can find or simulate

a statistical method for this.

And of course I have to point out that the boundary between Q1b and

Q1c is another catch-saying, QS46!

regards, Paul