What concept describes the likelihood of different outcomes from a random experiment?

The concept that describes the likelihood of different outcomes from a random experiment is the probability distribution. A probability distribution provides a mathematical function that describes the probabilities of the possible outcomes of a random variable. It essentially maps each outcome to a probability, encapsulating the behavior of the random variable and allowing one to understand how likely each result is.

For example, if you conduct a random experiment like rolling a die, the probability distribution would detail the probabilities assigned to each face of the die appearing, which in this case is uniform (1/6 chance for each face). Understanding the probability distribution is essential for making predictions and calculations regarding various scenarios based on randomness.

The other concepts are related but serve different purposes. Sample statistics refer to the summary measures computed from a sample that is taken from the population, such as the sample mean or sample proportion. Population parameters are the actual values that describe the entire population, such as the population mean or population standard deviation, which are typically unknown and estimated through sample statistics. The margin of error is a statistic that expresses the amount of random sampling error in a survey's results and is related to confidence intervals, not the description of likelihood from random experiments.