The cumulative probability distribution
In the last two exercises, we saw the probability distributions of a discrete and a continuous variable. In this exercise we will jump into cumulative probability distributions. Let's go back to our probability density function of the first exercise:
All the probabilities in the table are included in the dataframe probability_distribution which contains the variables outcome and probs. We could sum individual probabilities in order to get a cumulative probability of a given value. However, in some cases, the function cumsum() may come in handy. What cumsum() does is that returns a vector whose elements are the cumulative sums of the elements of the arguments. For instance, if we would have a vector which contains the elements: c(1, 2, 3), cumsum() would return c(1, 3, 6)
This exercise is part of the course
Basic Statistics
Exercise instructions
- Calculate the probability that a variable x is smaller or equal to two. Put the result in the variable
prob. You can use the values from the table displayed above. - Calculate the cumulative probability that a variable x is respectively 0, smaller or equal to one, smaller or equal to two, and smaller or equal to three. Use the
cumsum()functions for this and print the output to the console.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# probability that x is smaller or equal to two
#' probability that x is 0, smaller or equal to one,
#' smaller or equal to two, and smaller or equal to three