la condición matemática más desfavorable en los resultados esperados
English translation: the least favourable mathematical outcome for the expected results
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GLOSSARY ENTRY (DERIVED FROM QUESTION BELOW)
Spanish term or phrase:
la condición matemática más desfavorable en los resultados esperados
English translation:
the least favourable mathematical outcome for the expected results
Spanish to English translations [PRO] Science - Mathematics & Statistics
Spanish term or phrase:la condición matemática más desfavorable en los resultados esperados
Spain: research paper:
Se recogieron y analizaron cuestionarios válidos de 319 especialistas en psiquiatría y de 957 pacientes depresivos, muestras que permiten una alta precisión en la estimación de resultados (con un error aleatorio de ± 5,5% en la encuesta a psiquiatras, y de ± 3,2% en la encuesta a pacientes, para un intervalo de confianza [IC] del 95%, supuesta una selección aleatoria de los encuestados y la condición matemática más desfavorable en los resultados esperados: p = q = 0,5).
What is the correct turn of phrase for this? (not my field) In Google I'm seeing "favorable/unfavorable result conditions" but can't pin down the entire thing. Thanks!
-------------------------------------------------- Note added at 23 hrs (2011-02-24 19:20:58 GMT) --------------------------------------------------
Suppose, just for example, that depression comes in just categories "Mild", Moderate" and "Severe". A sample of 957 patients is taken to estimate the proportion of "Severe" cases in the population - suppose we find 189 "Severe" cases in the sample. That suggests about 20% of the population has severe depression (actually 19.7% = 189/957) . But that was only a sample, so the true value in the population may well be a bit more or less.
The question is "how much more or less?" and the study says ± 3.2%. Or to put it another way, we're 95% sure the true value is in the range [19.7-3.2, 19.7+3.2] = [16.6, 22.9]. This 95% is the "valor de significación".
What p is, is the estimated probability of having severe depression, i.e 0.197. And q is the estimated probability of NOT having severe depression i.e 1-0.197 = 0.803.
Finally, the ± 3.2% has been worked out based on the worst case scenario of p = q = 0.5 (logical if you think about it, it's hardest to discriminate if it's equally likely a person selected has or has not sever depression). So what they are saying is that 3.2 is conservative and, in practise, the range of [16.6, 22.9] can probably be reduced e.g. just to name a figure maybe it's really more like [18.0, 21.5] (still with 19.7 bang in the middle!)
yes, this is the idea and fits with what DLyons has given us. I was just imagining there might be a "set phrase" here that a statistician would know. But apparently it's just a matter of finding the least awkward way to say it.
This is not my field, but couldn't you say "assuming ... the least favourable mathematical outcome, where p = q = 0.5"? Presumably if p and q are equal, the study doesn't prove anything.
Automatic update in 00:
Answers
7 hrs confidence: peer agreement (net): +1
(assuming) the least favourable situation (that in which p=q=0.5.) for the expected results
Explanation: Discrimination is weakest where success probability = failure probability = 1/2.
-------------------------------------------------- Note added at 7 hrs (2011-02-24 02:27:26 GMT) --------------------------------------------------
-------------------------------------------------- Note added at 23 hrs (2011-02-24 19:20:58 GMT) --------------------------------------------------
Suppose, just for example, that depression comes in just categories "Mild", Moderate" and "Severe". A sample of 957 patients is taken to estimate the proportion of "Severe" cases in the population - suppose we find 189 "Severe" cases in the sample. That suggests about 20% of the population has severe depression (actually 19.7% = 189/957) . But that was only a sample, so the true value in the population may well be a bit more or less.
The question is "how much more or less?" and the study says ± 3.2%. Or to put it another way, we're 95% sure the true value is in the range [19.7-3.2, 19.7+3.2] = [16.6, 22.9]. This 95% is the "valor de significación".
What p is, is the estimated probability of having severe depression, i.e 0.197. And q is the estimated probability of NOT having severe depression i.e 1-0.197 = 0.803.
Finally, the ± 3.2% has been worked out based on the worst case scenario of p = q = 0.5 (logical if you think about it, it's hardest to discriminate if it's equally likely a person selected has or has not sever depression). So what they are saying is that 3.2 is conservative and, in practise, the range of [16.6, 22.9] can probably be reduced e.g. just to name a figure maybe it's really more like [18.0, 21.5] (still with 19.7 bang in the middle!)
DLyons Ireland Local time: 09:19 Specializes in field Native speaker of: English PRO pts in category: 54
Grading comment
With explanation way beyond the call of duty... thanks!
Notes to answerer
Asker: Thanks, DLyons. This being your specialty field, may I just ask you about the "p" here... is it the "valor de significación" P? or is it for "probability" or something else?
Asker: I mean, I think you said as much in your good explanation... just want to confirm. Thanks.
The translation workplace 
peer agreement (net): +1
