Trial vs Outcome
Both terms below come up in the same part of the course, and students mix them up. Here is each one defined on its own, side by side, so you can see where they part company.
Trial
Probability
A trial is one repetition of a chance process, such as a single coin flip or one spin, and it produces exactly one outcome.
Trials are the unit you count when you repeat a random process, and they are called independent when the result of one does not change the probabilities for the next. A simulation works by running many trials and tracking how often the event of interest shows up. Flip a coin 20 times and you have run 20 trials, each landing heads or tails; if 12 come up heads the relative frequency of heads is . The binomial setting is defined by a fixed number of independent trials that each have the same probability of success.
Outcome
Probability
An outcome is a single possible result of one trial, and the collection of every outcome for that trial is the sample space.
Outcomes are the smallest pieces of a chance process, and an event is just a set of outcomes grouped together because you care about them. Rolling a fair six-sided die has six outcomes, 1 through 6, and the event roll an even number is made of the three outcomes 2, 4, and 6, so its probability is . The probabilities of all the outcomes in a sample space always add to 1. Outcomes do not have to be equally likely, even though the die example happens to be.