Ordinal Data:

Ordinal data are discrete or  discontinuous consisting of categories of variable that  are ranked, ordered or compared according  to  a predetermined standard clothing size, teaching ranks, contest winner, are  all  ordinal data. A  ranking of patient behaviours according to how  often they occur during a given  period is another example. Although there are no  equal  intervals between points,  rank orders do have a relative order between categories, like first, second, third ranks  or ranked  as "always", "mostly", "sometimes", "rarely" and "never". 

The interval  or  ratio  data can  be  converted to ordinal  data according to magnitude of each score,  e.g.  score, of 81 to 100 may be called  'excellent', 61  to  80  as  'good',  41  to  60  as  'average',  21  to 40  as 'poor'  and  below 21 as 'very  poor'.  However, ordinal  data cannot  be  converted  to  interval  or ratio  level  data. Let us  see how  ordinal data would look  in  tabular form Take Abde1lah and Levine7s  attempt to create a graphic rating for assessing nursing care. The  categories are ranked  in  order from "care of the highest quality" to "very poor care" with varying degree of service between.