Jed: So you need only look at the positive results, and estimate the likelihood that every one of them was caused by incompetent researchers making mistakes. ***That is what I've been saying all along. Note how Joshua Cude just glides over it. The hallmark of a skeptopath is how disingenuous they can be.
O'Malley's calculation determines the probability of getting N hits in N tries. It's just wrong. ***No, no no. How many times do we need to go through this for a skeptopath to acknowledge it? The calculation assumes N tries and N hits, and then proceeds to calculate the probability of those N hits were ALL by some error or errors. On 5/16/13, Joshua Cude <[email protected]> wrote: > On Wed, May 15, 2013 at 5:08 PM, Jed Rothwell <[email protected]> > wrote: > >> Joshua Cude <[email protected]> wrote: >> >> >>> As I wrote, it represents the probability that ALL of the replications >>>> were the result of error. >>>> >>> >>> >> >>> No it doesn't. That is true only if all the attempts give replications. >>> Look up the binomial distribution, and find someone to explain it to >>> you. >>> >> >> I believe that would only apply if success or failure was random. >> > > You're not following the argument. The claim is that *If* the positive > results are from random errors, then the number of positive hits would be > very unlikely. But that's not true using 1/3 for the chance of a false > positive, because that fits pretty well with the success rate reported by > Hubler for example. If the probability of a false positive is 1/3, and you > run N experiments, you should expect something close to N/3 false > positives. O'Malley's calculation determines the probability of getting N > hits in N tries. It's just wrong. > > > > >> When a cathode fails in a properly equipped lab, they always know why it >> failed. They can spot the defect. When there are no defects and all >> control >> parameters are met, it always works. So you need only look at the >> positive >> results, and estimate the likelihood that every one of them was caused by >> incompetent researchers making mistakes. >> > > Storms himself says positive results depend on nature's mood. He said here: > "Of course it's erratic… created by guided luck." If you're calculating the > likelihood of a certain number of hits from errors, you have to consider > all the attempts, not just the successful ones. It's elementary. > > > I'm not saying Cravens' bayesian analysis is wrong, though I suspect the > assumptions are, but O'Malleys' simplistic analysis teaches us nothing. >
