Phrase: It has long been known
Translation: I haven't bothered to look up the reference
Phrase: It is believed
Translation: I think
Phrase: It is generally believed
Translation: A couple of other guys think so, too
Phrase: It is not unreasonable to assume
Translation: If you believe this, you'll believe anything
Phrase: Of great theoretical importance
Translation: I find it kind of interesting
Phrase: Of great practical importance
Translation: I can get some mileage out of it
Phrase: Typical results are shown
Translation: The best results are shown
Phrase: 3 samples were chosen for further study
Translation: The others didn't make sense, so we ignored them
Phrase: The 4 hour sample was not studied
Translation: I dropped it on the floor
Phrase: The 4 hour determination may not be significant
Translation: I dropped it on the floor, but scooped most of it up
Phrase: The significance of these results is unclear
Translation: Look at the pretty artifact
Phrase: It has not been possible to provide definitive answers
Translation: The experiment was negative, but at least I can publish the data somewhere
Phrase: Correct within an order of magnitude
Translation: Wrong
Phrase: It might be argued that
Translation: I have such a good answer for that objection that I shall now raise it
Phrase: Much additional work will be required
Translation: This paper is not very good, but neither are all the others in this miserable field
Phrase: These investigations proved highly rewarding
Translation: My grant is going to be renewed!
Phrase: I like thank Miller for assistance with the experiments and Perkins useful discussions on the interpretation of the data
Translation: Miller did the experiment and Perkins explained it to me
Charlie wrote: Are you in drug research too? :laugh:
Charlie
Have you ever read a drug study that wasn't written that way? 32 years of reading those things and no one would ever just say" It doesn't work very well".
Siscowet wrote: Have you ever read a drug study that wasn't written that way?
Not really, and I'm a co-author on several of them!
When analyzing data there are ways to discard outliers. The best is the 2.5 standard deviations outside the mean test, but in all my years working in drug research I have yet to see anyone use it! I have sat in on "data meetings" where the tech recited problems he had with an outlier sample, and the primary investigator eliminated it from the study based on what amounted to anecdotes. On several occasions this rose to the level of fraud! But those guys tend to get weeded out pretty quick .
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