Data types

[MG1:Chp 1, p1-p6]

Types of data

• Qualitative data
  * Data which describes some quality
  * e.g. gender, types of admission
• Quantitative data
  * Data which are measured on a numerical scale
  * e.g. pain scale, temperature

Categorical data

• Qualitative data are best summarised by grouping observations into categories
  --> Often referred to as categorical data or nominal data
• When there are only two categories, the data can also be called dichotomous data or binary data
  * e.g. gender

Ordinal data

• When there is an order among categories
  --> Ordinal data
  * Example: Pain score, ASA score
• There is no direct mathematical relationship with ordinal data
  * e.g. pain score of 6 is not really double that of a pain score of 3

Quantitative data

• Commonly referred to as numerical data
• Can be:
  * Discrete
  * Continuous
• Discrete numerical data can only be recorded as whole numbers
  * Is usually counted
  * e.g. episodes of MI, post-tetanic count
• Continuous data can be any value
  * Is usually measured
  * e.g. Temperature, body weight, respiratory rate

NB:

• Respiratory rate is a special case
  * Normally counted
  * But non-whole number values (e.g. 5.5 breath/min) is still meaningful

Interval and ratio scale

• Continuous data can be further divided into
  * Interval
  * Ratio scale
• Ratio scale is when the data has a true zero point and any two values can be numerically related
  * e.g. Temperature in Kelvin is ratio data --> 100 degrees Kelvin is twice that of 50 degrees Kelvin
  * e.g. Temperature in Celcius is NOT ratio data --> 100 degrees Celcius is NOT twice that of 50 degrees Celcius
  * e.g. Age is ratio scale