THE STATISTICAL APPROACH TO
DEFINING NORMALITY
According to the statistical approach to defining normality Normal
behaviour is any characteristic that is common in a large group. If
everyone does it, it must be normal!
The disadvantage is that not everyone is normal or average in all ways.
The statistical approach to defining normality suggests there are distinct
dividing lines between normal and abnormal behaviour
Some terms you will need to understand
Normal Distribution = behaviour in a large group of individuals that is
distributed in a particular way
Statistical Average = if the majority demonstrate a behaviour they make
this behaviour normal (If everyone does it, we class it as normal)
Statistical Extremity = if the minority demonstrate this behaviour they
make this behaviour abnormal (If hardly anyone does it, we class it as
abnormal)
Skewed Distribution = the results are unevenly distributed and cluster
and the high end (negatively skewed) or low end (positively skewed) of the
graph
Central Tendency = most results being in the middle
Mean (average) = average of all the individual scores
Average = add up all the scores / how many scores there are
Median = the middle score of the group
Mode = the most common score
Range = spread of scores between the highest and lowest.
Highest number-lowest number
Standard deviation = the average distance each score falls from the
mean