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Defining Experimental and Theoretical Probability

Defining Experimental and Theoretical Probability

Author: Laura Kniffin

This learning packet includes:

New Terms and Definitions
An introduction of common terms in probability, and examples of how they are used

New terms and a video explaining the probability of an event.

Co-author: Sara Gorsuch

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 Experiment: Is a situation involving chance or probability that leads to the results.

Outcome: Is the result of a single trial of an experiment.

Event: Is one or more outcomes of an experiment.

Probability: Is the measure of how likely and event is

Sample Space: The concept in probability theory, which considers all the possible outcomes for an event or experiment.

Sample Point: A single possible outcome that is a member of the sample space.

Event: Is any collection of outcomes in an experiment

Mutually Exclusive:  Two events that cannot possibly occur together.

Example: A subject cannot be both male and female, nor can they be age 20 and 30, but a subject could be both male and 30 or both female and 20.

All-Inclusive: The entire population, the entire sample falls into one category.  


Sampling With Replacement: The two sample values are independent, which means what we get on the first one does not affect what we get on the second.

Example: Rolling dice. (No matter what you get on the first roll, it does not affect what you can get on the second)

Sampling Without Replacement: The two sample values are dependent, which means what we get on the first one affects what we can get for the second one.

Example:  If I were drawing colors out of a hat and there was a certain amount of each color inside, each time I take out a color it affects the probability of me getting that same color. 

Random Sample: A random portion of the population being analyzed.



Probability of an Event

Try Probability Examples On Your Own.