Bayes' Theorem - Lab
Introduction
In this lab, you'll practice Bayes' Theorem in some simple word problems.
Objectives
In this lab you will be able to:
- Use Bayes' theorem to determine the probability of specific events
Define a custom function for Bayes' theorem
To start, write a function, bayes()
, which takes in the probability of A, the probability of B, and the probability of B given A. From this, the function should then return the conditional probability of A, given that B is true.
def bayes(P_a, P_b, P_b_given_a):
# Your code here
return P_a_given_b
Skin Cancer
After a physical exam, a doctor observes a blemish on a client's arm. The doctor is concerned that the blemish could be cancerous, but tells the patient to be calm and that it's probably benign. Of those with skin cancer, 100% have such blemishes. However, 20% of those without skin cancer also have such blemishes. If 15% of the population has skin cancer, what's the probability that this patient has skin cancer?
Hint: Be sure to calculate the overall rate of blemishes across the entire population.
# Your code here
0.46875
Children (I)
A couple has two children, the older of which is a boy. What is the probability that they have two boys?
# Your solution P(2boys|older child is a boy)
0.5
Children (II)
A couple has two children, one of which is a boy. What is the probability that they have two boys?
# Your solution P(2boys|1 of 2 children is a boy)
0.3333333333333333
A diagnostic test
A diagnostic test is advertised as being 99% accurate
-
If a patient has the disease, they will test positive 99% of the time
-
If they don't have the disease, they will test negative 99% of the time
-
1% of all people have this disease
If a patient tests positive, what is the probability that they actually have the disease?
# Your solution P(Disease | positive test)
0.5
Summary
In this lab, you practiced a few simple examples of Bayesian logic and how you can add prior information to update your beliefs about the chance of events.