I mistakenly thought the app was broken, but it isn’t. What I need to know again is rather, what Odds are you entering, not percentages. The calculator doesn’t use percentages. It uses odds.

For example, you can do it all by hand. Odds Form is easiest, rather than percentages, which is why the calculator is built that way. Basic formula is Final Odds (on Historicity) = Prior Odds x Likelihood Ratio. Prior Odds for you on the low end will be 1/10; high end, 99/1. For “Brother of the Lord” you then have to ask: how much more or less likely is that piece of evidence on historicity than on non-historicity, and enter the resulting odds.

For instance, in OHJ I put odds on this on the low end of 1/2, meaning this evidence is twice as likely on nonhistoricity than on historicity (given the peculiarities I note that are usually overlooked); but on the high end I put 2/1, meaning this evidence is twice as likely if Jesus existed than if he didn’t (and is therefore evidence for historicity), again for the reasons I articulate in the text.

So when you say the probability of the Brothers of the Lord data is 95-99%, what do you mean? If that’s the probability of that data on historicity? Or on nonhistoricity? The odds will be the ratio. So if you think that evidence is more likely on historicity (and thus is evidence for historicity), you might enter 99/95, but that would mean it is extremely weak evidence, making almost no difference to the question. More likely you want to say something like 3/1 or 2/1 or 10/1 or something (though whatever you choose, you have to be able to defend why you think that and not something else). On the high end. And on the low end maybe 1/1 or 2/1 or even 1/2 or 1/5 or whatever (ditto).

The calculator will give you results as percentages rather than final odds (it does the conversion for you). But if you do it by hand, you will get odds (converting that then to percentages is a task). So if you set the low end at 1/10 prior and 1/2 Brothers, your final odds will be 1/20, or 20 to 1 odds against historicity. Or if you set the low end at 1/10 prior and 2/1 Brothers, your final odds will be 2/10 = 1/5, or 5 to 1 odds against historicity. And if you set the high end at 99/1 prior and the high end for Brothers at 2/1, your final odds will be 198/1, or almost 200 to 1 odds in favor of Jesus existing.

Etc.

First, the Bayesian Calculator in CHRESTUS is Odds Form, so I’m not sure you are inputting correctly. When you say here “10%” as the prior for historicity, do you mean you entered odds of historicity of “1 in 10”? And when you say “99%,” that you entered “99 to 1”?

Second, when you say “Evidence 1: Brother of the Lord” etc. do you mean on historicity or on non-historicity? You have to enter two sets of values, one set of “best” and “worst” for each. I now just looked in the app, and its missing a whole section (the second one, i.e. the best and worst odds on non-historicity section, necessary for the calculator to work). So something is broken. I’ll get the tech on it ASAP. We’ll need to find the problem, fix the problem, then run updates on both platforms; all that can take a few weeks, alas.

Wait, no, ignore that second point. The app is working fine. It just requires Odds Form entries. See my comment on your second query.

Another round, this time really trying to make the strongest case, leaving out things like the silence of Paul/epistles:

Priors: worst 50% best 99%

Brother of the Lord
worst 95% best 99%

Mission:
worst 95% best 99%

Tacitus:
worst 80% best 95%

Overall – worst 26% best 48%

Wow, it’s really hard to get over 50%!

Can anyone who understands Bayesian reasoning explain why this happens?

Am I correctly using the Bayesian calculator on CHRESTUS?

Here’s my inputs; what I think are the strongest bits of evidence FOR Jesus.

Prior probabilities that Jesus existed:
worst case 10% best case 99%

Evidence 1: Brother of the Lord.
Worst case 95% best case 99%

(I wasn’t sure how to integrate my two assumptions here. I think it’s about 95% likely that Paul meant a fraternal brother, but also 5% likely that the Gal 2 passage is an interpolation.)

Evidence 2: Tacitus – which makes it into Dawkins’s new book as the best evidence FOR.

Worst case 20% best case 80%

(Considering possible interpolation vs Christians who knew the truth telling Tacitus that Jesus was historical)

Evidence 3: Silence of Paul/Epistles/Church fathers

Worst case 5% best case 50%

Why so low on both sides?
It’s not just Paul who seems to know little to nothing about Earthly Jesus. Even Irenaeus reports hearing Polycarp talking about seeing the Lord in an oddly detached manner:
“I can speak even of the place in which the blessed Polycarp sat and disputed, how he came in and went out, the character of his life, the appearance of his body, the discourses which he made to people, how he reported his intercourse with John and with the others who had seen the Lord, how he remembered their words, and what were the things concerning the Lord which he had heard from them, and about their miracles, and about their teaching, and how Polycarp had received them from the eyewitnesses of the word of life, and reported all things in agreement with the Scriptures.”

‘Seen the Lord’ is followed by stories only of THEIR miracles and THEIR teaching, but nothing about the miracles and teachings of Jesus. Odd!

The next 2 pieces are included because I asked the Prof of the History of Christianity at Oxford what he thought was the best evidence FOR historicity.

Evidence 4: The Christian Mission

Would there have been a Christian mission without a physical Jesus?

Worst case 33% Best case 95%

The worst case is based on the fact that if Jesus was a celestial being that makes THREE religions founded by angels, so Christianity would have a 1/3 chance of being one. (is this circular? It feels like maybe…)

I’m not sure what I’m doing with the best case number. I guess that reflects that angel-inspired missions don’t seem to be much barrier to a religion.

Evidence 4: Paul disagrees with Jesus about divorce.

My professor friend reckons Paul’s disagreement corroborates the teaching re divorce (NONE!) that is related in Matthew, which is nowhere in Scriptures, so would be new and therefore most likely from a real person.

Worst case 80% Best case 99%

I tried to make this one heavily in favour.

According to the calculator on CHRESTUS:

Overall: Worst case 0% Best case 27%

That’s still pretty low…I was surprised.

Could you please let me know if I have done something wrong?

Thanks!

It isn’t relevant. They can either accept the conclusions here argued and thus renounce what they previously argued, or reject them and be a Doofus.

So if you want to know which now it is, and for some reason still want to know, you should ask them.

Their Doofus statements I lift as examples—but don’t credit to them, since I am making a generic and not a personal argument—appeared on Facebook principally and are scattered and buried in complex threads in numerous places. It isn’t even worth your bother digging through all that. It’s easier to just ask them point blank: what do they think of the positions here argued and why. Then you’ll know straightaway whether they are still a Doofus or not.

In short, this is advice on how to detect a Doofus is for you, the reader. Not for them. They had their chance to learn all this already. I cannot tell you whether they learned that lesson by now.

I noticed a couple of comments in this article that mention Loftus and Miller, but unfortunately they don’t supply very much context and I wasn’t around during the time of the disagreement(s), so I can’t seem to figure out what they might have said. (E.g. I can’t find any quotes or links to their statements/articles. The one quote of the word “conceding” is again in reference to the “Not Be a Doofus” article, but I couldn’t find “conceding” at that article either.)

So, I’m just wondering if you could clarify or reference what the context of Loftus’ (and Miller’s I suppose 🙂 ) statements/arguments/articles/whatevers were? Maybe a quote, link, or even just an article title and/or date?

Oh, and in case reference to them was accidentally polished out of the “Doofus” article, I thought you might want to know about that.

It’s curious. A while back (several years now) I recall Loftus starting to take probability seriously, so I was kinda surprised to read that he seems to have thrown Bayes overboard. Would be interesting for me to get some perspective on how/where he went off track.

Cheers!

https://statmodeling.stat.columbia.edu/2019/04/12/several-reviews-of-deborah-mayos-new-book-statistical-inference-as-severe-testing-how-to-get-beyond-the-statistics-wars/#.XLElsVXf2Z8.wordpress

Another one: “800 Scientists Say It’s Time to Abandon ‘Statistical Significance’,” at Vox.

I don’t know what you mean by “Non-subjectivists.” All knowledge is subjective; there is no objective access to the real world outside the theatre of the mind. So I don’t know who you could be referring to. Perhaps this explains your whole problem: you seem not to understand what an epistemic probability is.

You also don’t seem to have a coherent point. There is no such thing as “events” that are not themselves the collection of billions of other events (or facts, as not all frequencies relate to time). What we choose to put in a set and call an “event” is an arbitrary human decision. So it is logically impossible that frequencies don’t apply to all sets however they are chosen. As soon as you select a set, that collection will have a frequency in background data.

Read Chapter 6 of Proving History to understand the nature of reference classing.

Meaning: even if one accepts that propositions have a probability, one still doesn’t get Bayesian notions out, if only because there are several notions of probability applied to propositions.

And I’m telling you all interpretations of probability either have no applicable use in human epistemology or reduce to the same definition applied in Bayesian probability theory: frequency. You have yet to present any evidence to the contrary, or even to address my deductive proof of this in Chapter 4 of Proving History.

The “imaging” (and other variants) folks do not deny the theorem (though it, but its application. For example, in the theory of projectiles one can calculate that the landing time of a projectile is negative.This is a theorem; however one denies that it applies to the world in the way the positive root of the equation does. One needs an argument for conditionalization as the rule.

I see no relevance of this to anything we are discussing.

If you are confusing idealized models (which are only useful fictions) with the complexity of real systems, you need to catch up.

As for calling Ville a crank, well, read the arguments: a (limit) frequency needs a collective. Collectives are not well defined, so probability is not a (limit of) frequency.

That is not a logically valid argument. You just stated a non sequitur.

Language requires words. Words are not well defined, so a language is not words.

If you think that’s a valid conclusion, you need a refresher on how logic works.

What sets we choose to demarcate and observe the frequencies of is arbitrary. That in no way affects the conclusion that probability is a frequency. This is to confuse semantics with application, and imprecision with error. So if this is what Ville is doing, he is an A-1 crank.

One needs limits to make sense of probabilities like 1/square root (2), which are vital in statistical and quantum mechanics and elsewhere because no finite collective works.

I see no relevance of this to Bayesian epistemology.

No human knowledge exists with an error margin smaller than an infinitesimal. So infinitesimal variances in probability are irrelevant to human epistemology.

If scientists want to get at such things by various devices (like limit theory), they are welcome to. But it has no bearing on epistemic probability. You thus seem to be confusing epistemic probability here, with objective frequencies in constructed models. Which gets us back to the start: you don’t know what epistemic probability is.

So called frequentist statistics do not require this assumption as far as I can tell.

Cite me an example of a peer reviewed frequentist work that derives an epistemic probability for a hypothesis from a probability calculation of 1/square root.

The mistake most make (perhaps you too – I don’t know) is something like: “we can estimate probabilities through a measurement of frequencies, therefore that’s what they are” – i.e., operationalism. But this is a mistake – it is somewhat like saying an electric current is an angle because that’s what an old school ammeter uses to show current intensity.

That’s a nonsense analogy.

You are confusing semantics again with applied model-making. Semantically, probability is synonymous with the affirmation of a frequency. Always and forever. In any context relevant to human epistemology (and all other contexts are irrelevant here, as we are discussing epistemology, not physical systems independent of it).

You might be uncomfortable with complex frequencies like 1/square root; most people are uncomfortable with infinitesimals. But that doesn’t make them “not” a frequency. These kinds of frequencies are of course already irrelevant to human epistemologies, which never deal in infinitesimal distinctions between probabilities, because no human precision comes anywhere near such a thing. But even if we wanted to explore imaginary situations, like some sort of god-being who can actually be infinitesimally certain of a frequency, all we are doing is dealing in transfinite frequencies. A frequency is a ratio, a rate: m to n. In no way does that require the ratio to be finite or rational. Any rate, like 1 black floor tile per every “square root of 1 square yard” of floor tiles, is still a frequency. How we would work with those awkward frequencies mathematically may involve certain limits and tricks or even be out of our means. But that doesn’t change semantically what that is: one tile per a given area; one photon per a given area; a.k.a. a frequency.

Even time ratios can be irrational, yet still a rate, a frequency: if we have a detector receiving one photon per second, and another detector beside it receiving one photon per square root of a second, we still have a ratio between them that is a frequency. But even the second rate is a frequency all by itself. That that second rate of photons doesn’t ever land “exactly” on a second mark on an arbitrary human clock is irrelevant. That human mathematical tools have a hard time running calculations with a frequency that off-kilter is only a limitation of our tools; it has no effect on what is being measured semantically, which is still a frequency.

Also worth checking is Nature’s latest article: Scientists Rise Up Against Statistical Significance.