How to use the word "Knowing" in statistics

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In summary, a vaccine has a 90% probability of preventing a certain disease. The probability of getting this disease if a person is not vaccinated is 50%. In a certain region, 25% of people get vaccinated against this disease.
  • #1
Biochemgirl2002
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A vaccine has a 90% probability of preventing a certain disease. The probability of getting this disease if a person is not vaccinated is 50%. In a certain region, 25% of people get vaccinated against this disease. Find the probability that a randomly selected person from this region

A. has the disease and was not vaccinated.
B. doesn't have the disease and was vaccinated.
C. has the disease.
D. wasn't vaccinated knowing that he/she has the disease

My attempt:
using a probability tree i made;
where V=Vaccinated (V^c = not vaccinated), D=has disease (D^c= doesn't have disease)

a) p(V^c)P(D|V^c)
=.75*.50
=0.375

b)P(V)P(D^c|V)
=0.25*0.90
=0.225

c) P(V)P(D|V)+P(V^c)P(D|V^c)
=(0.25*0.10)+(0.75*0.50)
=0.4

d) this is where i have the issue, what does the word Knowing mean? i assumed that i would just go ahead and do
P(V^c)P(D|V^c)
=0.75*0.50
=0.375
but since it says knowing, I am not sure if there is something else i have to do because they know they have the disease, maybe instead it would be 0 since they won't get vaccinated now that they have the disease?

[Moderator's note: Moved from a technical forum and thus no template.]
 
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  • #2
rhiana said:
D. wasn't vaccinated knowing that he/she has the disease
I interpret this to mean that the subject didn't get vaccinated because he/she already has the disease. A vaccination is supposed to prevent you getting its associated disease. If you know you have the disease, what's the point in getting a vaccination for it?
 
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  • #3
Mark44 said:
I interpret this to mean that the subject didn't get vaccinated because he/she already has the disease. A vaccination is supposed to prevent you getting its associated disease. If you know you have the disease, what's the point in getting a vaccination for it?
This is not my interpretation. The question is more likely intending to ask for the probability that a given person who has fallen ill was vaccinated. In other words: ”what is the probability that a person is vaccinated conditioned on that person having fallen ill”.

PS. This is a stupid question as it fails to account for population effects such as herd immunity.
 
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  • #4
rhiana said:
D. wasn't vaccinated knowing that he/she has the disease

d) this is where i have the issue, what does the word Knowing mean? i assumed that i would just go ahead and do
P(V^c)P(D|V^c)

A more common way to phrase the question in English is: What is the probability the selected person was not vaccinated given that he/she has the disease? This would make it clear that the student working the problem knows the person has the disease - instead of suggesting that the person selected knows that fact.

Your answer computed ##P(V^C \cap D)## , however question d) asks you to find ##P(V^C| D)##

On the site you mentioned in another thread: https://www.zweigmedia.com/RealWorld/tutorialsf15e/frames7_5.html

You can find that ##P(E|F) = \frac{ P(E \cap F)}{P(F)} = \frac{ P(F | E) P(E)}{P(F)}##

You can apply that rule to find ##P(V^C | D) ##
 
  • #5
Stephen Tashi said:
A more common way to phrase the question in English is: What is the probability the selected person was not vaccinated given that he/she has the disease? This would make it clear that the student working the problem knows the person has the disease - instead of suggesting that the person selected knows that fact.

Your answer computed ##P(V^C \cap D)## , however question d) asks you to find ##P(V^C| D)##

On the site you mentioned in another thread: https://www.zweigmedia.com/RealWorld/tutorialsf15e/frames7_5.html

You can find that ##P(E|F) = \frac{ P(E \cap F)}{P(F)} = \frac{ P(F | E) P(E)}{P(F)}##

You can apply that rule to find ##P(V^C | D) ##
oh! alright so the answer should be

P(V^c ∩ D) / (P(D))
=0.375/0.4
=0.9375
Is this correct?
 
  • #6
rhiana said:
=0.9375
Is this correct?

Yes
 
  • #7
rhiana said:
wasn't vaccinated knowing that he/she has the disease
Orodruin said:
PS. This is a stupid question as it fails to account for population effects such as herd immunity.
It's also a poorly formed question in that it is not clear who the subject is in the clause "knowing that he/she has the disease".
 
  • #8
I am going to step in with my standard method of solving problems like this, not using formulas.

Imagine a population of 1000 people. 25% of them, 250, get vaccinated. 90% of those, 225 do not get the disease, the other 10%, 25 people, do get the disease. Of the 750 people who do not get vaccinated, 50%, 375 get the disease, the other 375 do not.

Find the probability that a randomly selected person from this region
A. has the disease and was not vaccinated.
That is 375 people out of the original 1000 so is 0.375 as you say.

B. doesn't have the disease and was vaccinated.
That is 225 out of the original 1000 so is 0.225 as you say.

C. has the disease.
A total of 25+ 375= 400 out of the original 1000 so 0.4 as you say.

D. wasn't vaccinated knowing that he/she has the disease
A total 25+ 375= 400 people got the disease and 375 of those were not vaccinated so 375/400= 0.9375, again, exactly what you have. Well done!
 

Related to How to use the word "Knowing" in statistics

1. How do I define "knowing" in statistics?

In statistics, "knowing" refers to having a certain level of confidence or certainty about the accuracy of a statement or prediction. It is often associated with the concept of probability, where a higher probability of an event occurring means a greater level of "knowing."

2. What is the difference between "knowing" and "believing" in statistics?

The key difference between "knowing" and "believing" in statistics is the level of evidence or data supporting a statement or prediction. "Knowing" implies a higher level of confidence and certainty, while "believing" may be based on intuition or personal opinions.

3. How can I use "knowing" in statistical analysis?

In statistical analysis, "knowing" is used to determine the confidence level or margin of error associated with a particular result. This can be done through various methods such as hypothesis testing, confidence intervals, and p-values.

4. Can "knowing" be subjective in statistics?

Yes, "knowing" can be subjective in statistics as it is based on the interpretation and understanding of data. Different individuals may have varying levels of confidence or certainty about the same statement or prediction.

5. How can I improve my "knowing" in statistics?

To improve your "knowing" in statistics, it is important to have a strong understanding of statistical concepts and methods. This can be achieved through education, practice, and staying updated on new developments in the field. It is also helpful to critically evaluate data and results to ensure a reliable level of "knowing."

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