Data presentation: non spatial data

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Geographical skills revision
Data presentation- non spatial data
Tables- effective, simple, good for showing a large amount of data in a
concise way. However, they have little visual impact.
Diagrams- use images. Pictograms use symbols to represent values. Display
data in a simple and visually stimulating way. Can be exaggerated or
distorted and give vague displays of data.
Charts- more precise than tables or diagrams and are available in a vast
variety of forms. They are forms of proportional symbols as their length,
area or volume is proportional to the value of the data. They are easily
available on computer programs and are visually stimulating.
Bar chart- used for discrete or time series data. Simple, quick and give an
instant visual impression. Can be vertical or horizontal. Length of the bar is
proportional to its value. Width of bar can be misled over the value
represented by the bar. Gaps should be left between the bars or else the
chart is called a histogram.
Pie chart- used with percentage data to show parts of a whole set of data.
Visually stimulating. Too many sectors can make it look unprofessional. Hard
to use colours as they distract from the sector size. Difficult to label
sectors so they are easy to read. Only useful for percentage data.
Divided bar chart- used to show constituents of a whole. Must keep the
divisions in the same order if you want a comparison. Too many sections
makes it look unprofessional. Difficult to use lots of colours, not always
easy to compare.
Rose or star- used to show directions. Length of bar reflects frequency and
width. Time consuming to draw and takes time to read as 2 aspects are
shown.
Proportional circle, square, triangle- area of shape is proportional to the
square root of the data value. Can cope with large numbers. Time consuming
to calculate and draw. Not easy to compare accurately, scale complex to
draw.
Proportional sphere, cube or pyramid- area of the symbol is proportional to
the cube root of the data value. Copes with very large numbers and gives a
good visual appearance. Time consuming to calculate and draw. Not easy to
compare accurately, scale complex to draw.
Graphs- ideal of continuous data or when looking for patterns between 2 or
more variables. The X axis has the independent variable and the Y axis has
the dependent variable. The graph shows to what extent X causes or
influences Y. Types of graph include: line graph, scatter graph, multiple line
graph, triangular graph, compound graph and positive or negative graph.

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