UNIT 2 STRENGTHS AND WEAKNESSES OF DATA PRESENTATION

Technique / Use / Strengths / Weaknesses
Field sketches and photographs /
  • For anything you want an image of.
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  • Good memory tool, especially if accompanied with detailed annotations.
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  • Only show one view, at one point in time.
  • May not be an accurate representation of the area.

Sketch maps /
  • When a rough map of the study site is needed.
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  • Good memory tool, especially if accompanied with detailed annotations.
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  • May not be an accurate representation.

Maps with proportional symbols /
  • Bars, pies and symbols can be used and located in the relevant place.
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  • Good visual representation of data.
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  • The scale needs to be right so the symbol fits.

Flow lines, desire lines and trip lines /
  • Flow line – represent movement along a given route. Variable width along a given route.
  • Desire/trip lines – straight line on a map to represent the movement of goods and people from region to region (not a specific route)
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  • Good to show direction (all) and size of movement (flow).
  • They are able to give a good visual impression of movement (flow).
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  • Maps lack precise interpretation unless statistical data is added (flow).
  • Desire and trip lines are only interested in source and destination areas, there will convergence from a central location. Could be improved by altering width according to data.

Choropleth maps /
  • Often used for land values, population densities and crop yields, but are useful for a wide range of data.
  • Often done using colours, but can be don using lines in different directions.
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  • Visually effective, you can see clear spatial patterns.
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  • The whole of an area with one shading pattern appears to have the same density with no variations in it, but in reality this is not usually the case and there will be variations within each area.
  • They give the impression that the density changes abruptly at the boundary line of each area butt his will not happen in reality and changes are more likely to be gradual and to bear little relation to the boundary lines.
  • With line shading it’s difficult to draw lines accurately and it’s time consuming. With the colouring method, the shades of colouring are difficult to achieve, especially with a large number of classes unless more than one colour is used.

Isoline maps /
  • Can be used for any data set where there are specific locations.
  • Examples are contour maps, meteorological maps (isotherm - temperature, isobar - pressure, isohyets - rainfall and isohel - sunshine)
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  • Data can be represented without artificial area boundaries. Therefore changes in value occur smoothly and not abruptly.
  • This makes maps useful for interpreting general trends in distribution.
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  • Can be difficult to construct.
  • There is some element of guess work involved in the positioning of the isolines between values. This makes them rather subjective, especially if there is a lack of known values.

Dot maps /
  • Mainly used for population distributions, but can also show crop yields, livestock and mineral distributions.
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  • Good visual representation of distributions.
  • Allows the major features of a distribution to be shown.
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  • Lacks precise location and value of each individual item.
  • Too many dots will fail to be useful as they will all merge into one or too few and it will create the impression of emptiness.
  • Regular spacing of the dots is extremely difficult to achieve, as is accurate counting.
  • Areas can be missed out if they don’t conform to the scale.
  • Will only indicate general variations between areas.

Line (arithmetic) graphs /
  • Show changes over time or with distance.
  • Smooth line when changes are gradual or straight line to emphasise changes
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  • Can compare multiple continuous data sets easily
  • Interim data can be inferred from graph line.
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  • Only to be used with continuous data.

Long-sections and cross-sections /
  • Often used in relation to rivers.
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  • Long sections show a view of the whole length.
  • Cross sections show a view of a segment.
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  • Either section is more useful when the other is available.
  • Only a snapshot in time.
  • As it is mostly used for rivers in Geography, it is ahighly susceptible to weather and geological conditions.

Bar graphs /
  • Useful for absolute values and contrasts between areas and places.
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  • Good visual representation of statistical data.
  • Simple to construct and easy to understand.
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  • Graphcategories can be reordered to emphasize certain effects
  • Use only withdiscrete data
  • Limited space for labelling with vertical bar graphs

Scattergraphs /
  • Used to compare two sets of data.
  • Often used in combination with Spearman’s rank.
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  • It will show you a correlation between two data sets
  • Relatively easy to construct.
  • Shows data spread clearly and any anomalies stand out.
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  • Too few datapoints can produce skewed results, producing in correct graph analysis
  • Impossible to label data points, hard to ascertain exact values
  • Too many data points can quickly make graph unreadable
  • Cannot show relationship between more than two variables at once

Pie charts /
  • Useful for %’s, statistical data.
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  • Shows % of each segment.
  • Easy to draw.
  • They can be used to represent a wide range of statistical data and are visually very effective, as the contribution of each segment is easy to see.
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  • Too many segments make the graph cumbersome.
  • Calculation of the amounts is more difficult than the bar chart
  • If there are a lot of small segments then they are difficult to analyse.
  • No exact numerical data.
  • Hard to compare 2 data sets.
  • "Other" category can be a problem.
  • Total unknown unless specified.
  • Best for 3 to 7 categories.

Triangular graphs /
  • Show the relationship between three different components.
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  • Show relative importance which may not be easily apparent form a data table.
  • Shows clusters.
  • The dominant component in each case can be seen.
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  • Data must be in %.
  • Can be difficult to read and to construct.

Kite diagrams /
  • Used to show percentage change with distance.
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  • allow you to view how much of each species is there and where they are in relation to each other in a chart format
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  • can be tricky to construct and analyse accurately.

Radial diagrams /
  • Good when one variable is a directional feature.
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  • Theadvantage of radial diagrams in that they allow you to display several independent variables.
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  • These graphs have a limited use and can only be used with specific types of data, as the scale around the edge must be of a continuous nature.

Logarithmic graphs /
  • Large data sets or when the rate of change is more important than the actual amount.
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  • Very useful when a large range of data needs to be presented.
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  • Can be difficult to construct and analyse.

Dispersion graphs /
  • Shows a range of values in a data set.
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  • Visually effective as the full range of data can be seen together with the patterns and groupings of the data.
  • Particularly useful for making comparisons either between areas or at the same location over a period of time.
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  • Data must be in a form which can be placed along a number line.