Summary Descriptive and inferential statistics

DESCRIPTIVE + INFERENTIAL
STATISTICS
DESCRIPTIVE STATISTICS
MEASURES OF CENTRAL TENDENCY –

 Inform us about central (middle) values for a set of data.
 They are ‘averages’ – ways of calculating a typical value for a set of
data.
 An average can be calculated in different ways:
 MEAN – calculated by adding up all the scores and then dividing
by the number of scores.
→ makes use of all the values in the data in the final calculation.
→ can be unrepresentative of the data as a whole if there are
extreme values.
→ not appropriate for nominal data.
 MEDIAN – the middle value in an ordered list.
→ not affected by extreme scores.
→ not all values are reflected in the median.
→ not appropriate for nominal data.
 MODE – most common value in the data set.
→only method appropriate when the data is in categories
(nominal data) but can be used for all kinds of data.
→ not useful way of describing data when there are
several modes.
MEASURES OF DISPERSION -

 Inform us about the spread of data.
 RANGE – calculated by finding the difference between the
highest + lowest score in a data set.
→ easy to calculate.
→ may be affected by extreme values.
 STANDARD DEVIATION – expresses the spread of the data
around the mean.
→ more precise measure because all the values of the data are
taken into account.
 → HOWEVER – some characteristics of the data are not
expressed, such as the influence of extreme values.
GRAPHS –

 Provide a means of actually looking at the data + seeing the results
at a glance.
 BAR CHART – the height of the bar represents frequency.
→ suitable for words + numbers (all levels of
measurement).