sample space
In probability theory, the sample space of an experiment is a set that contains all possible outcomes. For example, when a basketball player shoots four free throws, the sample space includes every combination of hits (H) and misses (M). There are 4 throws, each with 2 possible outcomes, so the sample space has 2^4 = 16 sequences:
HHHH, HHMM, HHHM, HHMH, HMHM, HMMH, HMMM, MMMM, MMHH, MHHM, MHHH, MMHM, MHMM, MMHM, MMMH, MHMH.
In the second experiment, we only count the number of baskets out of 4, so the sample space includes 0, 1, 2, 3, or 4 baskets.
random experiment
A random experiment is any process that results in one of several possible outcomes in a way that cannot be predicted with certainty. The outcome is determined by chance.
For example, shooting a basketball is a random experiment because each shot can either be a hit or a miss.
Another instance is counting the number of baskets made in four free throws, another kind of random experiment that still depends on the player’s skill and the inherent randomness of the game.
combinatorics
Combinatorics is the branch of mathematics focusing on counting, arrangement, and combination of objects.
When we list the sequences of hits and misses for four basketball throws, we use combinatorics to determine there are 2^4 = 16 outcomes.
In another scenario, if we are counting the number of made baskets, combinatorics helps us understand the various ways 0, 1, 2, 3, or 4 hits can occur in any order.
independent events
Independent events are those whose outcomes do not affect each other. Each free throw in our exercise is an independent event.
Whether the player makes or misses one shot doesn’t change the probability of making or missing the next.
Understanding this helps us calculate the likelihood of different sequences in the sample space accurately.