Analysing and Presenting
Quantitative Data:
Descriptive statistics
Objectives
After this session you will be able to:
• Prepare quantitative data for analysis.
• Select appropriate formats for the
presentation of quantitative data.
• Choose the most appropriate techniques
for describing data (descriptive statistics).
Types of data
Measurement scales and their
uses
Types of question that yield
nominal data
Results of question yielding
nominal data
Type of question yielding ordinal
data
Results of question yielding
ordinal data
Results of question yielding
interval data
Results of question yielding
ratio data
Coding data
Dealing with missing data
Avoiding degradation of data
Typical approach
1.
Age
Better approach
2.
20 – 24
or
25 – 29
2.
30 – 34
40 – 49
50 – 54
55 – 64
65 +
Data degraded – we cannot even
calculate the mean age
Please state your age. ______
Please state your date of birth ______
Descriptive statistics: use of
charts for frequency data
Bar chart for nominal data
Pie chart for nominal data
Frequency data for age range
(interval) data
Histogram illustrating interval
data
Bar chart for nominal data with
comparison between groups
Stacked bar chart for nominal
data with comparison between
groups
Interval and ratio data –
comparing groups
Comparing two variables for a
single group
Descriptive statistics: frequency
distribution and central tendency
Measuring dispersion
• The range: The difference between the highest and the
lowest scores.
• The inter-quartile range: The difference between the
score that has a quarter of the scores below it, and the
score that has three-quarters of the scores below it (the
75th percentile).
• The variance: A measure of the average of the squared
deviations of individual scores from the mean.
• The standard deviation: A measure of the extent to
which responses vary from the mean. (Derived by
calculating the variation from the mean, squaring them,
adding them and calculating the square root.)
The normal distribution
Summary
• The selection of statistical tests should be made at the
design stage of the research and not as an afterthought.
• Data can be classified into categorical data (which
includes nominal and ordinal) and quantifiable data
(which includes interval and ratio). The types of data
yielded by a study will determine the kinds of analysis
and statistical tests applied to them.
• Data may be presented descriptively through the use of
pie charts, bar charts and histograms or through the use
of descriptive statistics. The latter focus on themes such
as the distribution of the data and its dispersion.