CPSY0900: Probability Distributions

What does a probability distribution describe?

the probability of all possible outcomes in an expeirment

Define discrete, continuous, and cumulative probability distributions

discrete: outcomes are distinct and finite (ex. rolling a dice)

continuous: outcomes that can take any value in a range; curves (ex. height, race time)

cumulative: the likelihood of a variable taking a value less than or equal to a specific value

What must all the probabilities in a distribution sum to?

1

What is the binomial distribution formula (see iPad notes) useful for calculating? 

the probabilities of events with 2 possible outcomes across multiple trials; ex. determining the probability of 4 heads (2 possible outcomes: heads and tails) on 12 total coin flips (trials: 12) 

What are conditional probabilities?

probabilities of one event given another event has already occurred (events are dependent)

What is Bayes’ Theorem?

a mathematical formula used to update the probability estimate for a hypothesis (or beliefs) as additional evidence is gained

ex. Monty Hall problem