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Deviation from the statistical norm

What is a deviation from the statistical norm and how does this help us to define mental health issues?
© Coventry University. CC BY-NC 4.0
What is statistical infrequency and how does this help us to define mental health issues?

The statistical approach

Researchers can use statistics to determine what is normal and abnormal.
Statistical definitions can be drawn on to determine whether an activity or psychological attribute deviates significantly from the statistical norm in society. If a someone is classed as normal they score in-line with the statistical norm whereas if they are ‘abnormal’ they display an attribute that appears infrequently in the statistics). For instance, when considering intellectual disability, if an IQ score is substantially under the norm of 100 this has been used in the past as one criterion.
A normal distribution curve for IQ among the population. This shows that 95.44% of the population have an IQ between 70 and 130, while 68.26% have one between 85 and 115. 2.28% have an IQ below 70 and 2.28% have an IQ above 130.
A graph showing the distribution of IQ among the population. The statistical norm is 100 (the peak of the graph). 68.26% of the population have an IQ between 85 and 115

Problems with the statistical infrequency approach

The statistical approach can be useful in helping us to determine a cut-off point in terms of diagnosis because anything that appears outside of the normal distribution curve is statistically rare behaviour. There are, however, still a number of problems with defining abnormality simply in terms of statistical infrequency.
First of all, this definition fails to distinguish between desirable and undesirable behaviour. It is only concerned with the frequency of it. For example, a high IQ is just as statistically abnormal as a very low one, but may well be regarded as highly desirable.
This definition also infers that the existence of abnormal behaviour in people should be rare or statistically unusual, which is not the case. Feelings of depression and anxiety that are highly prevalent in many mental health issues are not statistically rare (Davey, 2017). This is a further reason why statistical deviation is not an adequate way to define abnormality in mental health and mental health issues.
In addition, implementing a definition of abnormality that is formed upon statistics can misguide people to believe that it is empirically objective and measurable. However, a subjective judgment is being made whenever the line is drawn between what is considered to be abnormal and normal. Who decides what is statistically rare and how do they decide? For example, if an IQ of 70 is the cut-off point, how can we justify saying someone with 69 is abnormal, and someone with 70 normal? (McLeod 2018).
Finally, exhibiting some form of prolonged abnormal behaviour at some point is common. This definition does not distinguish between rare, slightly odd behaviour and rare, psychologically abnormal behaviour (Faudemer et al. 2015) .
As we have seen, using statistical methods to ascertain normality and abnormality can help us to understand how behavioural patterns are distributed through a population of people, but taken alone, this method might not be nuanced enough to define a person’s mental health as normal or abnormal. Just because a behaviour is statistically unusual, is it ‘abnormal’?

Your task

  • Can you think of any contexts where it could be useful for healthcare professionals to use the statistical infrequency method?
  • Are there situations where this might not be as useful?
Post your thoughts in the comments area.


Davey, G.,C. (2017) Psychopathology. 2nd edn. Chichester: Wiley
Faudemer, K., Hayden, C., McHale, K., and Simson, C. (eds.) (2015) A-Level Psychology: AQA Complete Revision and Practice. Newcastle Upon Tyne: CGP Books
McLeod, S. (2018) ‘Abnormal Psychology’ [online]. available from https://www.simplypsychology.org/abnormal-psychology.html [16th November 2018]
© Coventry University. CC BY-NC 4.0
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Defining Mental Health: A Short Introduction

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