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Parameter
a numerical measurement describing some characteristic of a population

Statistic
a numerical measurement describing some characteristic of a sample

Quantitative (or numerical) data
consists of numbers representing counts or measurements.
Example: The weights of supermodels
Example: The ages of respondents

Categorical (or qualitative or attribute) data
consists of names or labels (representing categories).
Example: The gender (male/female) of professional athletes
Example: Shirt nmbers on professional athletes uniformssubstitutes for names.

Discrete data
result when the number of possible values is either a finite number or a 'countable' number (i.e. the number of possible values is 0,1,2,3,...)
Example: The number of eggs that a hen lays

continuous (numerical) data
result from infinitely many possible values that correspond to some continuous scale that coers a range of values without gaps, interruptions, or jumps.
Example: The amount of milk that a cow produces; e.g. 2.343115 gallons per day.

Nominal level
characterized by data that consist of names, labels, or categories only, and the data cannot be arranged in an ordering scheme (such as low to high).
Example: Survey responses yes, no, undecided.

Ordinal level
involves data that can be arranged in some order, but differences between data values either cannot be determined or are meaningless.
Example: Course grades A,B,C,D, or F

Interval level
involves data that can be arranged in order and the difference between any two data values is meaningful,. However, there is no natural zero starting point (where none of the quantity is present)
Example: Years 1000, 2000, 1776, and 1492

