NOMINAL LEVEL DATA

SEE ALSO WHY DOES IT MATTER WHAT SORT OF DATA YOU HAVE?

The categories are often given designated numbers: No=0, Yes=1.

EXAMPLE: in a sample of 40 people, 22 answered Yes to a given question (coded 1) and the other 18 people answered No (coded 0).

Gender (male=0, female=1),

Marital Status (single=0, cohabiting=1, married=2, separated=3, divorced=4, widowed=5), Profession (psychologist=1, psychiatrist=2, occupational therapist=3),

Main Disorder (Anxiety=2, Depression=1, None=0).

NB: The designated numbers here have no meaning other than to distinguish one category from another. In the last example above, 'anxiety' could have been labelled 1 and 'depression' 2. However, the categories 'No' and 'None' are often labelled '0' because it is easy to remember if the coding scheme is not written on questionnaires when you are entering data from them.

YOU CAN ALSO GET NOMINAL DATA WHEN YOU ARE -

Coding qualitative materia: Another important example of nominal Data are the coding of qualitative material, such as lines of text from a written record of a tape-recorded interview, or answers written on a comment section of a postal questionnaire.

e.g. The following codes numbered 1 to 7 might be created for client comments about a therapy service received: