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reply re: point #2
::::::The third replay experiment was similar in design but clearly, not the same in some aspects. As I noted previously, their plating densities were higher in the third experiment. That was an change in the experimental conditions. Blount et al. noted that the results produced a smaller number of mutants than expected -- assuming the conditions really were comparable -- but apparently, the conditions were not effectively the same.--[[User:Argon|Argon]] 20:52, 31 July 2008 (EDT)
::::::The third replay experiment was similar in design but clearly, not the same in some aspects. As I noted previously, their plating densities were higher in the third experiment. That was an change in the experimental conditions. Blount et al. noted that the results produced a smaller number of mutants than expected -- assuming the conditions really were comparable -- but apparently, the conditions were not effectively the same.--[[User:Argon|Argon]] 20:52, 31 July 2008 (EDT)
::::::: You write, "but apparently, the conditions were not effectively the same." That's known as circular reasoning. You can't accept that the mutations do not scale, and so you insist that somehow the conditions "apparently" must have been significantly different. Under your approach, you'd insist there must have been a significant difference in the experiments no matter what the evidence is or what the paper says (it says they were similar).--[[User:Aschlafly|Aschlafly]] 20:57, 31 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.