Measures of Central Tendency:
Mean –
χ=
∑χ
n
Pros: takes into account all values, easy
Cons: can be skewed by outliers or anomalies
Mode –
Most common value
Bi-modal and tri-modal sets
Pros: good for categoric data, easy
Cons: not entirely accurate (crude data)
Median –
Middle number
Technique: put into order, calculate middle number
Pros: not affected by outliers/anomalies
Cons: less sensitive than mean
Measures of Dispersion:
Range –
Highest – lowest
Pros: easy
Cons: doesn’t take into account middle numbers
Standard deviation –
A measure of the spread of data around the mean
Pros: takes into account every value
Cons: unduly affected by extreme scores.
Mean –
χ=
∑χ
n
Pros: takes into account all values, easy
Cons: can be skewed by outliers or anomalies
Mode –
Most common value
Bi-modal and tri-modal sets
Pros: good for categoric data, easy
Cons: not entirely accurate (crude data)
Median –
Middle number
Technique: put into order, calculate middle number
Pros: not affected by outliers/anomalies
Cons: less sensitive than mean
Measures of Dispersion:
Range –
Highest – lowest
Pros: easy
Cons: doesn’t take into account middle numbers
Standard deviation –
A measure of the spread of data around the mean
Pros: takes into account every value
Cons: unduly affected by extreme scores.
