Changes

:: Your reply to the second point is unresponsive to the flaw.  You seem to completely misunderstand it, or hope others do.  Any fixed "mutation rate" should scale with sample size, yet the data prove otherwise.--[[User:Aschlafly|Aschlafly]] 22:22, 27 July 2008 (EDT)

:: Your reply to the second point is unresponsive to the flaw.  You seem to completely misunderstand it, or hope others do.  Any fixed "mutation rate" should scale with sample size, yet the data prove otherwise.--[[User:Aschlafly|Aschlafly]] 22:22, 27 July 2008 (EDT)

::: If you're growing several of the same kind of plant in two different pots, one would expect that under the same conditions total stem growth would scale with sample size (number of plants in the pot). But would you still expect that if one pot received ample water, light and fertilizer while the other was unfertilized in dry, dim conditions? That's an extreme example, but nonetheless you wouldn't expect plants to grow the same way under different conditions. Also in this example, mutation rates in the plants would differ, since one pot received more radiation while the other contained plants that were less healthy and therefore less able to repair DNA damage- different environments lead to different pressures. So, once more, cells, be they bacteria or part of a multicellular plant, do not grow or "behave" the same way under different circumstances, and for someone always claiming that everyone else is erroneously grouping the experiments, you consistently keep doing it yourself here.[[User:Kallium|Kallium]] 23:06, 27 July 2008 (EDT)

:::Previous comment removed by [[User:Kallium|Kallium]] 09:01, 30 July 2008 (EDT)

:::: The paper plainly states, "The third replay experiment was similar in design to the second, but on a larger scale."  So I don't know why you imply that the experiments were significantly different.  Yet the results from the second and third experiments do NOT scale with sample size, thereby disproving any plausible type of fixed mutation rate.--[[User:Aschlafly|Aschlafly]] 23:22, 29 July 2008 (EDT)

:::: The paper plainly states, "The third replay experiment was similar in design to the second, but on a larger scale."  So I don't know why you imply that the experiments were significantly different.  Yet the results from the second and third experiments do NOT scale with sample size, thereby disproving any plausible type of fixed mutation rate.--[[User:Aschlafly|Aschlafly]] 23:22, 29 July 2008 (EDT)

:3)The claim that the use of Monte Carlo resampling test was an error is unsupported by argument or counterclaim. ''Why'' is the use of that test an error? Problematically, if the test itself is invalid, why are you willing to accept the p-value for the third replay? Furthermore, the Monte Carlo test was not the test used to combine the three experiments to arrive at the final p-value of p<0.0001 - that was a Z-transformation method. Perhaps your real objection lies with this technique rather than the Monte Carlo test.

:3)The claim that the use of Monte Carlo resampling test was an error is unsupported by argument or counterclaim. ''Why'' is the use of that test an error? Problematically, if the test itself is invalid, why are you willing to accept the p-value for the third replay? Furthermore, the Monte Carlo test was not the test used to combine the three experiments to arrive at the final p-value of p<0.0001 - that was a Z-transformation method. Perhaps your real objection lies with this technique rather than the Monte Carlo test.

:::If you can formalize your objection to the Monte Carlo resampling, then by all means do so and include it in the letter - with a reference, if possible. This is an honest suggestion, not sarcasm. Something along the lines of 'With one million resamplings without replacement, the Monte Carlo technique will potentially underestimate the p-value by x% if the probability of an event is below y; see Statistician et al, 1997'. If you're basing your acceptance of the null hypothesis on some other statistical technique that gives you some other p-value, then you should report the technique and the p-value. If you think that the Monte Carlo technique gives a lower bound to the p-value, such that it must be higher than 0.08, then say so.

:::If you can formalize your objection to the Monte Carlo resampling, then by all means do so and include it in the letter - with a reference, if possible. This is an honest suggestion, not sarcasm. Something along the lines of 'With one million resamplings without replacement, the Monte Carlo technique will potentially underestimate the p-value by x% if the probability of an event is below y; see Statistician et al, 1997'. If you're basing your acceptance of the null hypothesis on some other statistical technique that gives you some other p-value, then you should report the technique and the p-value. If you think that the Monte Carlo technique gives a lower bound to the p-value, such that it must be higher than 0.08, then say so.

:4)It was not 'an error' to include later generations in the replay experiments, because those generations provide information that bears on the contingency hypothesis- they can indicate if the contingency 'window' closes. It would be a valid request that the authors provide an explicit description of the techniques used to exclude the presence of occult Cit+ cells from the samples used in the replay experiments. At some point you will have to accept or reject that it is ''possible'' to do so, routinely, using basic laboratory techniques. If you accept that it is possible, the only way to prove that the routine procedures failed is to repeat the experiment with more rigorous controls and show a different result. Otherwise your objection boils down to "because I said so". If you reject categorically that it is possible to screen all Cit+ cells out, then all of microbiology comes into question, because these are truly fundamental techniques used across thousands of labs for many, many years.

:4)It was not 'an error' to include later generations in the replay experiments, because those generations provide information that bears on the contingency hypothesis- they can indicate if the contingency 'window' closes. It would be a valid request that the authors provide an explicit description of the techniques used to exclude the presence of occult Cit+ cells from the samples used in the replay experiments. At some point you will have to accept or reject that it is ''possible'' to do so, routinely, using basic laboratory techniques. If you accept that it is possible, the only way to prove that the routine procedures failed is to repeat the experiment with more rigorous controls and show a different result. Otherwise your objection boils down to "because I said so". If you reject categorically that it is possible to screen all Cit+ cells out, then all of microbiology comes into question, because these are truly fundamental techniques used across thousands of labs for many, many years.

::::He's only asking if you're affiliated with you mother's organization. It's a fair question, it seems to me, and not a very far leap of logic. [[User:Corry|Corry]] 23:57, 29 July 2008 (EDT)

::::He's only asking if you're affiliated with you mother's organization. It's a fair question, it seems to me, and not a very far leap of logic. [[User:Corry|Corry]] 23:57, 29 July 2008 (EDT)