Probability Bayes formula Question

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SUMMARY

This discussion focuses on solving two probability problems using Bayes' theorem and binomial distribution. The first problem involves determining the number of programmers, n, needed to ensure a 99.8% probability that at least one detects an error, given each has a detection probability of 0.875. The second problem evaluates a tuberculosis skin test's effectiveness, requiring the calculation of conditional probabilities using Bayes' formula, specifically P(T|P) and P(T|¬P), where T is the event of having tuberculosis and P is the event of a positive test result.

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  • Understanding of binomial distribution and its parameters.
  • Familiarity with Bayes' theorem and conditional probability.
  • Basic knowledge of probability notation and mathematical symbols.
  • Ability to perform calculations involving probabilities and percentages.
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  • Study the binomial distribution and its applications in probability problems.
  • Learn how to apply Bayes' theorem in various scenarios, particularly in medical testing.
  • Practice calculating conditional probabilities using real-world examples.
  • Explore common pitfalls in interpreting probability results, especially in diagnostic testing.
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Students in statistics, data analysts, healthcare professionals evaluating diagnostic tests, and anyone interested in applying probability theory to real-world problems.

crays
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Hi guys, I've got 2 probability questions that i couldn't solve. Please help.

1) A computer program has an error that causes the program not to function perfectly. n programmer are assigned separately to detect the error. The probability that each programmer will detect the error is 0.875. Determine the value of n if the probability that at least one programmer detects the error is 0.998


2) A new skin test is devised for detecting tuberculosis. To evaluate the test before it is put into use, a research indicates tuberculosis in 96% of those who have it and in 2% of those who do not. It is known that 8% of the population has tuberculosis.

a) Find the probability of a randomly selected person having tuberculosis given that the skin test is positive.

I've gotten this right, Its (Have tuberculosis|Test is positive) so what i did was using (0.96 x 0.08) + (0.02 x 0.92) the value for all test is positive. Then 0.96 x 0.08 divide by the value i just got, i got the answer right.

b) Find the probability that a person has tuberculosis given that the test indicates no tuberculosis is present.

What i had in mind is to reverse the probability for all test is positive and get all test is negative and do the same, but it wasn't right.

c) Find the probability of the skin test giving a false positive result.

Please help :) Thanks
 
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You would do well to use symbols and equations. For part (a) if you let X = number of programmers finding the error then X is binomial with parameters n and p = .875. You are looking for P(X ≥ 1) which is 1 - P(X = 0) to be .998.

For the second part, again, use some mathematical notation.

Let P be the event the test is positive
Let T be the event the patient has tuberculosis.

In part (a) you were calculating P(T|P) using the (unwritten) Bayes formula. To make your solution readable you should write:

P(T|P) = \frac {P(P|T)P(T)}{P(P|T)P(T) + P(P|\overline{T})P(\overline{T})} =

and put your numbers in after the = sign.

For (b) you are asking for P(T|\overline{P}). If you will begin by writing out the formula for that you may see how to calculate it. Using the formulas can make all the difference.
 

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