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2. Based on the information presented, some of the patients have MSLT data that could be misleading and others do not. For the following statements, select Yes if the scenario provided would change that status for any of the five patients. Otherwise select No.

Shouldn't the answer be
Yes
No
Yes
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Question 3: For the following statements, select True if the statement is inferable from the data provided. Otherwise select False.
  • 60% of the participants had a mean sleep latency of less than 8 minutes. TRUE: Ramesh, Sara and Steve
x/5=60/100 --> meaning 3 patient. 
Ramesh --> approx 1,6
Sara --> approx 4,4
Angel --> approx 9 NO
John --> approx 8,2 NO
Steve --> approx 7,2
  • Only one of the five patients had results that indicate severe excessive daytime sleepiness. --> "and latencies shorter than 5 minutes are taken to indicate severe excessive daytime sleepiness". Based on the previous results should be Sara and Ramesh so there are 2 and not 1 so is FALSE.
 
  • It is possible that Sara suffers from fatigue rather than excessive daytime sleepiness.­ TRUE
Yes because "Use of prescription medications such as stimulants or antidepressants can also lead to misleading results" and she is taking stimulants. 
 ­
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Question 3: For the following statements, select True if the statement is inferable from the data provided. Otherwise select False.

  • 60% of the participants had a mean sleep latency of less than 8 minutes.
x/5=60/100 --> meaning 3 patient. 
Ramesh --> approx 1,6
Sara --> approx 4,4
Angel --> approx 9 NO
John --> approx 8,2 NO
Steve --> approx 7,2

  • Only one of the five patients had results that indicate severe excessive daytime sleepiness. --> "and latencies shorter than 5 minutes are taken to indicate severe excessive daytime sleepiness". Based on the previous results should be Sara and Ramesh so there are 2 and not 1.
 

  • It is possible that Sara suffers from fatigue rather than excessive daytime sleepiness.­
Yes because "Use of prescription medications such as stimulants or antidepressants can also lead to misleading results" and she is taking stimulants. 
 ­
Isn't first and third statement misleading, then how can we infer that?? please explain.­
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Can someone explain Q3 since if the MSLT results are misleading, then how can statement 1 be True and statement 2 be False?

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Can someone explain Q3 since if the MSLT results are misleading, then how can statement 1 be True and statement 2 be False?

Posted from my mobile device
­I tried to explain it in the thread, have you seen it?
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Nice effort on the explanation but still can't understand how statement 1 is true for the 3rd question since if the MSLT results are misleading then how can Sara's readings be accurate? The readings are accurate for Ramesh and Steve based on the conditions in tab 2.

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In question 3
If the data is misleading based on the prescription medication one is taking then how can I ascertain Sara actually suffers from any sleeping disorder? Please can someone help.
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In question 3
If the data is misleading based on the prescription medication one is taking then how can I ascertain Sara actually suffers from any sleeping disorder? Please can someone help.
­Since the question asks about the probability and don't claim it
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Tab 3 mentions data for 4 of 6 patients may be misleading. The 1st statement in Q3 asks if 3 out of 5 patients have low latency. Indeed 3 of them have it but 2 of them are those patients whose data might be misleading. So can we still infer 60% have low latency

Krunaal please help
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Rohit_842
Tab 3 mentions data for 4 of 6 patients may be misleading. The 1st statement in Q3 asks if 3 out of 5 patients have low latency. Indeed 3 of them have it but 2 of them are those patients whose data might be misleading. So can we still infer 60% have low latency

Krunaal please help

Hi Rohit_842, can you point me to where it says 6 on tab 3? I see 5 patients and 5 times.
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Rohit_842
Tab 3 mentions data for 4 of 6 patients may be misleading. The 1st statement in Q3 asks if 3 out of 5 patients have low latency. Indeed 3 of them have it but 2 of them are those patients whose data might be misleading. So can we still infer 60% have low latency

Krunaal please help
Even though the data could be misleading, we need to infer from the MSLT results that we got, else it will be an assumption - and as you mentioned indeed 3 of them have a mean less than 8 minutes.
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Rohit_842
Tab 3 mentions data for 4 of 6 patients may be misleading. The 1st statement in Q3 asks if 3 out of 5 patients have low latency. Indeed 3 of them have it but 2 of them are those patients whose data might be misleading. So can we still infer 60% have low latency

Krunaal please help

Sorry, I did not find 6 anywhere.


You can solve this question a few ways:
  1. Quick and dirty (and probably good enough)
  2. Detailed and long (and you can still make a mistake)

I would recommend Quick and Dirty.

I did not do the other 2 questions so it is possible that some of this calculations would have been already done but if you approach this question as a PS, You will be doing a lot of calculations to calculate mean/average for 5 people with 5 parameters. That's annoying esp with minute and second conversions, so I did quick and dirty. However to do the quick and dirty, you have to have read and understood all of the 3 conditions/questions.


  1. Ramesh
    • Nap times: 1:45, 3:10, 1:24, 2:05, 1:30
    • Approx Average 2 or so minis (actual is 1.98 if you care)
    • Conclusion: below 5 minutes
  2. Sara
    • Nap times 5:34, 4:34, 5:45, 3:45, 5:05
    • Approx Average: hard to determine. This sucks because we have to figure out the exact number to rule below or above 5 mins), so 334 + 274 + 345 + 225 + 305 = 296.6 mins, just under 5 mins.
    • Conclusion: below 5 minutes but very close.
  3. Angel
    • Nap times: 10:32, 8:34, 7:45, 9:22, 11:23
    • Approx Average is likely 10 mins and definitely way above 8.
    • Conclusion: above 8 minutes
  4. John (Kid - may be affected by the note)
    • Nap times: 8:34, 9:23, 5:56, 9:34, 10:23
    • Approx Average over 8 mins in my view without doing a recalculation.
    • Conclusion: this is above 8 minutes
  5. Steve
    • Nap times: 6:23, 7:45, 8:34, 7:56, 8:10
    • Approx Average: has to be below 8 mins because we have 40 secs from 8:34, 7:56, and 8:10 to distribute to 6:23 and 7:45, so below 8.
    • Conclusion: between 8 and 5 minutes
Using these five averages:

  1. 60 % of the participants had a mean sleep latency of less than 8 minutes.
    Three of the five (Ramesh, Sara, Steve) have means under 8 minutes, which is 60 %. TRUE
  2. Only one of the five patients had results that indicate severe excessive daytime sleepiness.
    Actually 2 patients (Ramesh and Sara) average under 5 minutes, which qualifies as severe, not one. FALSE.
  3. It is possible that Sara suffers from fatigue rather than excessive daytime sleepiness. - Trickiest Question.
    The guidelines say someone who falls asleep in under 2 minutes is unlikely to be merely fatigued or exaggerating. Sara’s mean is greater than 2 minutes, so we are not told that we can rule out fatigue. We are also told that using a stimulant may lead to misleading results. TRUE.

Sorry for the typo, I meant tab 3 mentions data of 3 out of 5 patients is misleading. Which means even if Ramesh, Sara, Steve have means under 8 minutes data for Sara and Steve MAY be misleading. And this is where I'm having a doubt can we still infer this. Its like saying for example I have 5 friends A, B, C, D, E aged 1, 2, 3, 4 and 5 respectively, however ages for B, C and D may be inaccurate. So can we infer 3 of my friends are aged below 4? Need your guidance Krunaal
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Sorry for the typo, I meant tab 3 mentions data of 3 out of 5 patients is misleading. Which means even if Ramesh, Sara, Steve have means under 8 minutes data for Sara and Steve MAY be misleading. And this is where I'm having a doubt can we still infer this. Its like saying for example I have 5 friends A, B, C, D, E aged 1, 2, 3, 4 and 5 respectively, however ages for B, C and D may be inaccurate. So can we infer 3 of my friends are aged below 4? Need your guidance Krunaal
The phrase in question stem "inferable from the data provided" means: based on the given data in the table as it stands - not based on whether the data may or may not be accurate. Even if the table says data "may be misleading", the inference question is testing your ability to read and interpret what is provided - not to second-guess or correct the data.

Let's say, taking your example - If you tell me that your 5 friends have ages: A=1, B=2, C=3, D=4, E=5, but also say that ages for B, C, D may be inaccurate, my job (in this question) is not to guess whether they’re correct - only to report based on the numbers you've given. So I would say: "According to the given data, 3 out of 5 friends are aged below 4." It might turn out later that the data is wrong - but based on what's in front of me, the inference is correct.

Hope it helps.
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Krunaal I'm not convinced on some aspects of Q3. Note that the STEM says: "For the following statements, select True if the statement is inferable from the data provided. Otherwise select False."

So we really need to consider all the data given to us by all the tabs. This means the table in Tab 3 has to be taken along with the information about misleading cases.

“60% of the participants had a mean sleep latency of less than 8 minutes.”

From raw math, yes (3/5 = 60%).

But per Tab 3, only Ramesh’s results are clearly reliable. The others may be misleading.

So we cannot infer this as true with confidence.
Answer: False.
Note that the statement is asking us to check if it's 100% accurate, it doesn't say likely, possiblity etc, so we should consider the possiblity of data being misleading hence we can't be sure that "60% of the participants had a mean sleep latency of less than 8 minutes"

“Only one of the five patients had results that indicate severe excessive daytime sleepiness.”


Raw math: 2 patients (Ramesh, Sara) are <5 min.

But Sara’s results are invalid because of prescription stimulant.

Only Ramesh has valid severe EDS results.
Answer: True.
If the statement had been "Only one of the five patients is likely to actually suffer from severe excessive daytime sleepiness", maybe then the answer would be False?


“It is possible that Sara suffers from fatigue rather than excessive daytime sleepiness.”

Tab 1: “Mean latency ≤ 2 min → unlikely fatigue. > 2 min → fatigue possible.”

Sara’s mean is ~4:57 → >2 min. Plus stimulant use makes results unreliable.
Answer: True.
This one seems to fit.

I think the official answers should either by changed or the statements be refined to match them.
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bb


Sorry, I did not find 6 anywhere.


You can solve this question a few ways:
  1. Quick and dirty (and probably good enough)
  2. Detailed and long (and you can still make a mistake)

I would recommend Quick and Dirty.

I did not do the other 2 questions so it is possible that some of this calculations would have been already done but if you approach this question as a PS, You will be doing a lot of calculations to calculate mean/average for 5 people with 5 parameters. That's annoying esp with minute and second conversions, so I did quick and dirty. However to do the quick and dirty, you have to have read and understood all of the 3 conditions/questions.


  1. Ramesh
    • Nap times: 1:45, 3:10, 1:24, 2:05, 1:30
    • Approx Average 2 or so minis (actual is 1.98 if you care)
    • Conclusion: below 5 minutes
  2. Sara
    • Nap times 5:34, 4:34, 5:45, 3:45, 5:05
    • Approx Average: hard to determine. This sucks because we have to figure out the exact number to rule below or above 5 mins), so 334 + 274 + 345 + 225 + 305 = 296.6 mins, just under 5 mins.
    • Conclusion: below 5 minutes but very close.
  3. Angel
    • Nap times: 10:32, 8:34, 7:45, 9:22, 11:23
    • Approx Average is likely 10 mins and definitely way above 8.
    • Conclusion: above 8 minutes
  4. John (Kid - may be affected by the note)
    • Nap times: 8:34, 9:23, 5:56, 9:34, 10:23
    • Approx Average over 8 mins in my view without doing a recalculation.
    • Conclusion: this is above 8 minutes
  5. Steve
    • Nap times: 6:23, 7:45, 8:34, 7:56, 8:10
    • Approx Average: has to be below 8 mins because we have 40 secs from 8:34, 7:56, and 8:10 to distribute to 6:23 and 7:45, so below 8.
    • Conclusion: between 8 and 5 minutes
Using these five averages:

  1. 60 % of the participants had a mean sleep latency of less than 8 minutes.
    Three of the five (Ramesh, Sara, Steve) have means under 8 minutes, which is 60 %. TRUE
  2. Only one of the five patients had results that indicate severe excessive daytime sleepiness.
    Actually 2 patients (Ramesh and Sara) average under 5 minutes, which qualifies as severe, not one. FALSE.
  3. It is possible that Sara suffers from fatigue rather than excessive daytime sleepiness. - Trickiest Question.
    The guidelines say someone who falls asleep in under 2 minutes is unlikely to be merely fatigued or exaggerating. Sara’s mean is greater than 2 minutes, so we are not told that we can rule out fatigue. We are also told that using a stimulant may lead to misleading results. TRUE.
For Question 3
Only one of the five patients had results that indicate severe excessive daytime sleepiness.
Actually 2 patients (Ramesh and Sara) average under 5 minutes, which qualifies as severe, not one. FALSE.

Wont we only consider Ramesh as a patient because Sara has asthma thus her results can be misleading. So the answer should be True

Please explain.
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WaguriSan

For Question 3
Only one of the five patients had results that indicate severe excessive daytime sleepiness.
Actually 2 patients (Ramesh and Sara) average under 5 minutes, which qualifies as severe, not one. FALSE.

Wont we only consider Ramesh as a patient because Sara has asthma thus her results can be misleading. So the answer should be True

Please explain.
2n statement says “...had results that indicate severe excessive daytime sleepiness.

We are not judging whether Sara truly has the disorder. We are judging what her test results show. Her average was under 5 minutes, so her results show severe excessive daytime sleepiness.

The note about medication only says that results can be misleading, not that they should be excluded.

Therefore, the statement “only one of the five patients had results that indicate severe excessive daytime sleepiness” is false because both Ramesh and Sara’s results fit the severe range.
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Hi,

I would like to add something here

For Q3) B and Q3) C

Although you arrived at the right answer

But I think there are some considerations which were missed

For Q3)B, You say that RAMESH and SARA have mean < 2 and therefore this is no

but the thing is, the answer is "NO" more precisely because the data states that the 4 patients except Ramesh can have misleading results

it can very well be that Sara's MSLT is more than 2

while someone else's MSLT falls under 2

For Q3)B

Since, we have no conclusive results on Sara

we can say that her mean might not fall under 2

and in that case she may not suffer from excessive daytime sleepiness

also just because her means >2 , does not mean she is fatigued

you cannot derive this from the statement, ie, if <2 = not fatigue
then >2 = fatigue

not inferrable

but statement is still a yes, cause of the misleading results of Sara which may lead us to conclude diff things
bb


Sorry, I did not find 6 anywhere.


You can solve this question a few ways:
  1. Quick and dirty (and probably good enough)
  2. Detailed and long (and you can still make a mistake)

I would recommend Quick and Dirty.

I did not do the other 2 questions so it is possible that some of this calculations would have been already done but if you approach this question as a PS, You will be doing a lot of calculations to calculate mean/average for 5 people with 5 parameters. That's annoying esp with minute and second conversions, so I did quick and dirty. However to do the quick and dirty, you have to have read and understood all of the 3 conditions/questions.


  1. Ramesh
    • Nap times: 1:45, 3:10, 1:24, 2:05, 1:30
    • Approx Average 2 or so minis (actual is 1.98 if you care)
    • Conclusion: below 5 minutes
  2. Sara
    • Nap times 5:34, 4:34, 5:45, 3:45, 5:05
    • Approx Average: hard to determine. This sucks because we have to figure out the exact number to rule below or above 5 mins), so 334 + 274 + 345 + 225 + 305 = 296.6 mins, just under 5 mins.
    • Conclusion: below 5 minutes but very close.
  3. Angel
    • Nap times: 10:32, 8:34, 7:45, 9:22, 11:23
    • Approx Average is likely 10 mins and definitely way above 8.
    • Conclusion: above 8 minutes
  4. John (Kid - may be affected by the note)
    • Nap times: 8:34, 9:23, 5:56, 9:34, 10:23
    • Approx Average over 8 mins in my view without doing a recalculation.
    • Conclusion: this is above 8 minutes
  5. Steve
    • Nap times: 6:23, 7:45, 8:34, 7:56, 8:10
    • Approx Average: has to be below 8 mins because we have 40 secs from 8:34, 7:56, and 8:10 to distribute to 6:23 and 7:45, so below 8.
    • Conclusion: between 8 and 5 minutes
Using these five averages:

  1. 60 % of the participants had a mean sleep latency of less than 8 minutes.
    Three of the five (Ramesh, Sara, Steve) have means under 8 minutes, which is 60 %. TRUE
  2. Only one of the five patients had results that indicate severe excessive daytime sleepiness.
    Actually 2 patients (Ramesh and Sara) average under 5 minutes, which qualifies as severe, not one. FALSE.
  3. It is possible that Sara suffers from fatigue rather than excessive daytime sleepiness. - Trickiest Question.
    The guidelines say someone who falls asleep in under 2 minutes is unlikely to be merely fatigued or exaggerating. Sara’s mean is greater than 2 minutes, so we are not told that we can rule out fatigue. We are also told that using a stimulant may lead to misleading results. TRUE.
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