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Bayes Theorem is crucial for a data scientist, so try to consolidate knowledge!
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Imagine that we decided to conduct medical research. You gathered data about two groups of people: 750 people with heart problems and 800 people with chronic stomachache. You know that 7% of interviewed from the first group have diabetes; meanwhile, 12% of respondents from the second group have diabetes too. Calculate the probability that a randomly selected person with diabetes has a chronic stomachache.
- Calculate the probability that a randomly selected person has a heart problem.
- Calculate the probability that the randomly selected person has a stomachache.
- Calculate the probability that you randomly select a person that has diabetes.
- Calculate the probability that a randomly selected person with diabetes has a chronic stomachache (already done).
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Bayes Theorem is crucial for a data scientist, so try to consolidate knowledge!
Swipe to start coding
Imagine that we decided to conduct medical research. You gathered data about two groups of people: 750 people with heart problems and 800 people with chronic stomachache. You know that 7% of interviewed from the first group have diabetes; meanwhile, 12% of respondents from the second group have diabetes too. Calculate the probability that a randomly selected person with diabetes has a chronic stomachache.
- Calculate the probability that a randomly selected person has a heart problem.
- Calculate the probability that the randomly selected person has a stomachache.
- Calculate the probability that you randomly select a person that has diabetes.
- Calculate the probability that a randomly selected person with diabetes has a chronic stomachache (already done).
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Completion rate improved to 3.7single
