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Table of Contents

 


Levels of Data 

There are four levels of variables.  These levels are listed below in order of their precision.  It is essential to be able to identify the levels of data used in a research design. They are directly associated with determining which statistical methods are most appropriate for testing research hypotheses.  

 

Nominal:  Classifies objects by type or characteristic (sex, race, models of vehicles, political jurisdictions)

Properties:

1.       categories are mutually exclusive (an object or characteristic can only be contained in one category of a variable)

2.       no logical order

Ordinal:  classifies objects by type or kind but also has some logical order (military rank, letter grades)

Properties:

1.       categories are mutually exclusive

2.       logical order exists

3.       scaled according to amount of a particular characteristic they possess

Interval:  classified by type, logical order, but also requires that differences between levels of a category are equal (temperature in degrees Celsius, distance in kilometers, age in years)

Properties:

1.       categories are mutually exclusive

2.       logical order exists

3.       scaled according to amount of a particular characteristic they possess

4.       differences between each level are equal

5.       no zero starting point

Ratio:  same as interval but has a true zero starting point (income, education, exam score).  Identical to an interval-level scale except ratio level data begin with the option of total absence of the characteristic.  For most purposes, we assume interval/ratio are the same.


 

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