To begin Statistical Inference, to measure uncertainty ...
Probability (definition): is a measure of likelihood or chance, expressed as a number (or %) between 0 and 1 (or 0% and 100%).
We use information from a sample to make inferences about a population (where info is generally unknown) based on probabilities or likelihoods of events.
Get familiar with the terminology in statistics!
An experiment is a process that allows us to obtain observations. Examples of experiments -- flipping a coin, tossing a die, choosing a card, etc. Ask yourself, how many total possible outcomes? When flipping a coin, there are 2 outcomes (heads or tails).
An event or outcome is the collection of results of an experiment. [Note the difference between a simple event (example: a 4 of clubs) vs. a compound event (example: a club).] How many events are there when tossing a die? Answer -- 6 events.
A sample space is the set of all possible simple events for an experiment.
S = {1, 2, 3, 4, 5, 6} when tossing a die, where e1 = 1, e2 = 2, e3 = 3, and so on ...
Then the probability of an outcome, say the probability of rolling a die and getting a 1 is written as P(1) = 1/6 and also consider that P(1) = P(2) = P(3) = P(4) = P(5) + P(6) = 1/6 if all outcomes are equally likely.
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