diff --git a/1-Introduction/04-stats-and-probability/README.md b/1-Introduction/04-stats-and-probability/README.md index 3a4a4ae9..43cb4103 100644 --- a/1-Introduction/04-stats-and-probability/README.md +++ b/1-Introduction/04-stats-and-probability/README.md @@ -25,7 +25,7 @@ In the case of discrete random variables, it is easy to describe the probability The most well-known discrete distribution is **uniform distribution**, in which there is a sample space of N elements, with equal probability of 1/N for each of them. -It is more difficult to describe the probability distribution of a continuous variable, with values drawn from some interval [a,b], or the whole set of real numbers ℝ. Consider the case of bus arrival time. In fact, for each exact arrival time $t$, the probability of a bus arriving at exactly that time is 0! +It is more difficult to describe the probability distribution of a continuous variable, with values drawn from some interval [a,b], or the whole set of real numbers ℝ. Consider the case of bus arrival time. In fact, for each exact arrival time *t*, the probability of a bus arriving at exactly that time is 0! > Now you know that events with 0 probability happen, and very often! At least each time when the bus arrives!