Independent - a variable that is expected to influence the dependent variable in some
Talk about the nominal level of measurement - Nominal - Categories simply used for
Order of variable values is irrelevant as one is not "higher" or "lower" than the other, just
Hair color (brown, red, black, blonde).
Political Party (Democrat, Republican, Libertarian, other).
Wine preference (Merlot, Cabernet, Pinot Noir, Chardonnay).
Nominal has two requirements. It must be mutually exclusive and exhaustive.
Nominal ranks qualities of units, not quantities.
What does it mean to be mutually exclusive? What about exhaustive? - Mutually
exclusive means that each case fits into no more than one category. Thus, you
shouldn't be able to check multiple boxes in a mutually exclusive question. Exhaustive
means that the variables has a category for every case. Thus, the question should
cover each possible situation - for example, listing each year of school and graduate
student as options, not just the undergrad years.
Each of the three levels of measurement must be mutually exclusive and exhaustive!
What are the three levels of measurement? Discuss how they relate to one another. -
Nominal, ordinal, and interval. All three must be exhaustive and mutually exclusive. It is
a one way staircase when comparing. When you have an interval/ratio variable, you can
go down to an ordinal variable, and then down to a nominal variable. But you can NOT
go up from nominal to ordinal or ordinal to interval/ratio.
Talk about the ordinal level of measurement - Like nominal variables, ordinal must also
be mutually exclusive and exhaustive. However, ordinal does have some inherent order,
meaning that we can say one category is higher or lower than another. Examples
include grades, health level, educational degrees.
Talk about the interval level of measurement - Like nominal- and ordinal-level variables,
must be exhaustive and mutually-exclusive.
Like ordinal-level variables, the categories must also have inherent order.
But, now we know the specific distance between categories.
The distance between all pairs of adjacent categories are the same.
Not just whether one category is higher or lower, but also by how much higher or lower
Ex: temperature, IQ scores.
Further, we also have these Ratio variables which meet all the requirements of an
interval measure and have a true 0 point. Examples include, height, age, and length of