Predicting burglary conviction rate
There are many situations that can be modeled with only two outcomes: success or failure. This exercise presents a situation that can be modeled with a binomial distribution and gives you the opportunity to calculate probabilities using binom.pmf()
, binom.cdf()
, and binom.sf()
.
The binom
object from scipy.stats
has been loaded for your convenience.
Imagine that in your town there are many crimes, including burglaries, but only 20% of them get solved. Last week, there were 9 burglaries. Answer the following questions.
This exercise is part of the course
Foundations of Probability in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# What is the probability of solving 4 burglaries?
four_solved = binom.____(k=____, n=____, p=____)
print(four_solved)