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Statistics in Orthopaedics

Data Type    Description    Discrete/Continuous    Qualitative/Quantitative    Non-Parametric/Parametric
Nominal    categories without order (eye colour, marital status)    Discrete   Qualitative    N
Ordinal    Ordered categories (Ficat classes)    Discrete Qualitative    N
Integer    Number of counts (papers)    Discrete Quantitative    P/N
Ratio    value independent of units    Continuous Quantitative   P/N
Interval    Distances betw. units are known (hours spent studying)    Continuous Quantitative P/N

Parametric Test = assume that the data were sampled from a particular form of distribution, such as a normal distribution; Non-Parametric = makes no such assumption. 


Always plot data. If data is presented always ask if it has been tested for normality, skewness & kurtosis (to determine need for parametric or non-parametric analyses)

Measures of Central Tendency:

  • Mean - average
  • Median - central value; use for ordinal data
  • Mode - value with most frequency; use for nominal data

Normal (Gaussian) Distribution:

  • Continuous symmetric distribution that follows the familiar bell-shaped curve
  • The distribution is uniquely determined by its mean and variance
  • Allows for Parametric tests (which are more powerful)
  • Rarely occurs in Orthopaedics
  • Skewed distribution:
    • Non-symmetrical, with a tail
    • easily seen by plotting data
    • use median or mode rather than mean
    • if in doubt assume non-normality & use non-parametric tests.
  • Kurtosis: 
    • is a measure of the heaviness of the tails in a distribution, relative to the normal distribution. 
    • A distribution with negative kurtosis is light-tailed relative to the normal distribution
    • A distribution with positive kurtosis is heavy-tailed relative to the normal distribution


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