Random variables and distributions
Discrete and continuous models, their parameters, and the named distributions the course uses.
8 terms
Binomial distributionThe binomial distribution gives the probability of a set number of successes in a fixed number of independent trials with a constant success probability.Empirical ruleThe empirical rule says that in a normal distribution, about 68, 95, and 99.7 percent of values fall within 1, 2, and 3 standard deviations of the mean.Expected valueThe expected value of a random variable is its long-run average, found by multiplying each value by its probability and adding the products.Normal distributionThe normal distribution is a symmetric, bell-shaped density curve described by its mean and standard deviation.Probability distributionA probability distribution lists every value a random variable can take along with the probability of each value or range of values.Random variableA random variable assigns a numerical value to each outcome of a chance process, so its value is determined by the result of a random event.Standard normal distributionThe standard normal distribution is the normal distribution with mean 0 and standard deviation 1, on which z-scores are read.t-distributionThe t-distribution is a symmetric, bell-shaped curve with heavier tails than the normal, used for inference about a mean when the population SD is unknown.