Generalizability is also referred to as [Type here].

The ideal type of sample is the [Type here], in which every member of the population has an equal chance of being selected into the study.

Believing that there is an association between number of years married and hair loss in men exists when no such association exists is an example of a(n) [Type here].

This sampling technique is faster, easier, and cheaper but less generalizable: [Type here].

Inferential statistics, also referred to as [Type here], helps us to determine the [Type here] of a given outcome.

In statistics, we are interested in [Type here], the likelihood of an event occurring, based on the actual outcome of many trials.

In reference to probability, [Type here] refers to the outcome for which we're trying to determing the probability.

After we analyze data, we do one of two things. List the two options:

[Type here].

[Type here].

Both proportions and probabilities are written as [Type here].