                    # 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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