Tobin wrote:Tobin wrote:When trying to show a correlation such as this, adding multiple subsets to the data does not help your results. If the Book of Mormon is really a work of fiction and not historical as claimed then the intellectually honest thing to do would be to make the case as simply and clearly as possible with something such as birth dates. That by itself should be more than sufficient to demonstrate the contention is true.
That is not what they did with the Book of Mormon. What you are championing and what the authors did is take many events from only a portion of the Book of Mormon history, put them all in one basket and claimed they were as a result made-up by a human-being. But any critical review of your results naturally blows up in your face because of the apparent bias that was introduced in your sample (comparing many different events together that may not even meet the criteria of being a random event). That is not how scientists or scholars should work. It is sloppy and unprofessional.
cognitiveharmony wrote:Why did you even respond? You've said nothing new. Your argument here is just as defeated as it was 3 posts ago. Until you respond with something substantive, I'll be ignoring you.
Fascinating. So instead of justifying this clear case of selection bias here and unprofessional behavior, you just say you'll ignore the apparent issues. I seriously doubt you even know what intellectual honesty means.
It pains me to respond to this since there is obviously nothing substantive in this post either. I guess I should have completely dispelled all of your assertions once again in my last post.
First of all, a collection of random subsets based on one common correlation such as the "day of the month" would be expected to be random as a whole in the EXACT same manner that each individual subset is random. This expectation of randomness would neither INCREASE nor DECREASE when these subsets are combined. Are you following me? This is a very simple premise and if you can't understand this then we're at an impasse. The ONLY argument that you have in this case is to prove that the event in any of these subsets would NOT be expected to be random in a historical context. You can't. We can take each specific event type and look at that type in a historical context and immediately see a random pattern on how they fall in the month such as an assassination of a leader :
Lincoln Apr. 15th
Kennedy Nov. 22nd
King jr Apr. 4th
Malcom X Feb. 21st
John Lennon Dec. 8th (not exactly a political leader but I couldn't think of anyone else when compiling this list)
Of course you could argue selection bias for this list because it is a subset of a larger list and I admittedly just looked up 5 of the most well known assasinations and I couldn't prove that it wasn't. But it can only be argued as selection bias because I've left out KNOWN data. Once all KNOWN data is included, the possibility of selection bias is ruled out.
Second of all, you have completely either misunderstood the analysis, or you are purposely misrepresenting it to make your case for selective bias. They did NOT take "many events" from "only a portion of the Book of Mormon history", they did in FACT take ALL of the events that actually had a day of month specified in the text (which is essential for this analysis) from the ENTIRE Book of Mormon history. In addition to this, every date except for 2 actually had more than 1 year separating them which increases the expectation of randomness. Do you even know what selection bias is? I would advise you to review this for your own benefit.
Third of all, your're suggestion that they should have used something such as birth dates for their analysis is asinine considering that there were no birth dates described in the Book of Mormon text specifying a day of the month. I was seriously laughing when I read that because I was contemplating if you might actually be joking. Obviously not.
Clear case of selection bias? Ridiculous. You can argue that the Book of Mormon is in fact the 1 historical book in 2000 but you can't argue the expectation of randomness.