Probabilistic interpretation of simulation

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I read a post on https://stackoverflow.com/questions/59441973/systematic-error-in-python-stochastic-simulation, and there's a part in the code that I'm having trouble understanding.

Within the code, there's a statement that if r > R, where R represents the probability of birth and r is a randomly drawn number, it suggests that a death occurred in the system. I'm confused about the rationale behind this interpretation. Can you help me, please?

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r = np.random.random() returns a (uniformly distributed) value $r \in [0,1)$. If $R$ is the probability of birth, then if this random value is in $[0, R)$ the code adds a birth, and if it's in $[R, 1)$ then the code adds a death.

That is, the code is mimicking the process of performing lots of trials and trying to simulate randomness, since $r$ falls in $[0, R)$ with probability $R$ and in $[R, 1)$ with probability $1-R$.