Types of Data

1. Categorical
   1. Nominal (eg, dz names, gender, Yes/No data points)
   2. Ordinal
2. Numerical
   1. Interval
   2. Ratio

Types of Data can also be classified into discrete or continuous.

Discrete data:

• has a finite set of values
• cannot be subdivided (rolling of the dice is an example, you can only roll a 6, not a 6.5!)
• a good example are binomial values, where only two values are present, for example, a patient develops a complications, or they do not

Continuous data:

• has infinite possibilities of subdivisions (for example, 1.1, 1.11. 1.111 etc.)
• an example I used was the measure of blood pressure, and the possibility of taking ever more detailed readings depending on the sensitivity of the equipment that is being used
• is mostly seen in a practical manner, i.e. although we can keep on halving the number of red blood cells per litre of blood and eventually end up with a single (discrete) cell, the absolutely large numbers we are dealing with make red blood cell count a continuous data value

Summary

• Nominal categorical = naming and describing (eg. gender)
• Ordinal categorical = some ordering or natural ranking (eg. pain scales)
• Interval numerical = meaningful increments of difference (eg. temperature)
• Ratio numerical = can establish a base-line relationship between the data with the absolute 0 (eg. age)

Norminal Categorical Data

characterized by name only; the names are mutually exclusive