Deviance from statistical norms

Behaviours, emotional reactions and patterns of thinking which are statistically rare (atypical) or deviate from the statistical average or norm are classified as abnormal. The statistical definition hinges on the idea that abnormality can be measured using quantitative data and thus one individual can be compared with another. Statistical norms are established using a normal distribution curve which illustrates the fact that most people, (approx 95%) score between one and two standard deviation above or below the mean average. This leaves just over 2% of people who score unusually high or low and these people would be classed as abnormal because they are not typical of most people.
When diagnosing depression for example, a structured interview or questionnaire including closed questions may be used and quantitative data can be derived; once the practitioner has calculated the individual’s ‘score’, this can be compared to statistical norms and a decision made about whether the person has a score which is high/low enough to be classed as abnormal.
With regard to intelligence the standard deviation is 15 and the average is 100, this means that anyone who scores over 130 or under 70 will be classed as abnormal since these scores are two standard deviations above and below the mean.
How will we learn about this definition in the classroom?
To prepare for your class, you will also need to to consult the following handout:…Statistical infrequency handout.doc
In class we will complete the following activities:
How can we evaluate this definition?

Revising this definition

exam technique practice – don’t be andre: Deviance exam technique
Revising skewed distribution