Data presentation

Data

Quantitative data records quantities (e.g. numbers, sizes, frequencies).

Qualitative data records subjective qualities (e.g. opinions and attitudes).

Discrete data can only take certain values (e.g. whole numbers)

Continuous data can take any value (e.g. length, width, time)

Justifying your choice of data presentation

Your findings can be presented with a range of graphical and mapping techniques. Each form of data presentation needs to be justified. Here is an example.

Fieldwork technique	Systematic sampling along a transect from the Peak Land Value Intersection to the edge of the CBD. An environmental quality score was calculated at every 30 metres.
Data presentation	Bar graph with distance from PLVI on x-axis and environmental quality score on y-axis.
Bad justification	The bar graph shows how environmental quality changes as distance increases from the PLVI.
Good justification	A bar graph is appropriate because both distance from the PLVI and environmental quality score are numerical and discrete categories.

Bar charts

Bar charts are used to show the numbers of things (or frequency) in several categories

Plot the categories on the x-axis
Leave gaps between the bars as data are not continuous (called discrete data)

Cross-sectional area bar chart — Example of a bar chart. The x-axis is not continuous.

Divided bar charts

Divided bar charts are used to show the frequency in several categories, like ordinary bar charts. It is a type of compound bar chart. But unlike ordinary bar charts, each category is subdivided.

Plot the categories on the x-axis
Leave gaps between the bars as data are discrete data
Use colours or shading to show the subdivided categories, and include a key

number of vehicles bar chart — Example of a divided bar chart: a key is included.

Percentage bar charts

Percentage bar charts are used to show the percentage of each subdivision in several categories. It is a type of compound bar chart.

Plot the categories on the x-axis
Leave gaps between the bars as data are discrete data
Use colours or shading to show the subdivided categories, and include a key
Each bar should be the same height (i.e. 100%)

% of vehicles bar chart — Example of a percentage bar chart, using the same data as the divided bar chart above.

Histograms

Histograms are used to show the numbers of things (or frequency) along a continuous scale

Plot the sliding scale on the x-axis
Do not leave gaps between the bars as data are continuous data

pebbles river histogram — Example of a histogram. The x-axis is continuous.

Pie charts

A pie chart is a circle divided into sectors. Each sector represents a percentage.

Sectors can be shaded or coloured, and need labels or a key
Multiple pie charts can be used where the size of each circle shows ratio.

Pebbles pie chart — Example of a pie chart.

Line graphs

Both axes are numerical and continuous i.e. each data point could be any value along the scale.
If time is one of the variables, always plot it on the x-axis.

Example of a line graph: both variables are continuous – each data point could be any value along the scale.

A river channel profile: a special and unusual line graph. Because we are showing the shape of the cross section we can join the points up despite it not being continous data as we are using the measurements to predict the truth.

Scatter graphs

This needs one independent variable (on x-axis) and one dependent variable (on y-axis).
Both axes must show ordinal data.
Do not join up each point: use a line of best fit instead, if appropriate.