Visual Presentation Lies, damned lies, and statistics? (Disraeli) Contributors Shelly Bradford EMPHO Helen Cooke SWPHO Sean McPhail SWPHO.

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Presentation transcript:

Visual Presentation Lies, damned lies, and statistics? (Disraeli) Contributors Shelly Bradford EMPHO Helen Cooke SWPHO Sean McPhail SWPHO

What you should learn Some examples of good presentation Some of bad presentation Some do’s and don’ts

Principles of good presentation Keep it simple Don’t present unnecessary information –eg unnecessary decimal places –repeated information All graphs must have –titles –labelled axes –timeframe –source

“Excellence in statistical graphics consists of complex ideas communicated with clarity, precision” (Tufte) Graphical displays should Show the data Reveal substance rather than methodology Avoid distortion

Napoleon’s route to Moscow, and return “The best statistical graphic ever drawn“ Tufte

Napoleon’s trip to Moscow

Patients per GP What are the limitations of this presentation?strangemaps.wordpress.com

You can’t see Cuba! 170 patients per GP

Main causes of death, Canada, 1971 NB area of each pie represents the number of deaths in that age-group

Risk assessment “You are hundreds of times more likely to have a crash on the way to the procedure than have a significant one during it”

The inclination and distortion that produce the 3D effects make it difficult to interpret the data. In the right view the Hazelnuts (4%) and the Cashews (8%) look the same. Avoid 3D distortion whenever possible

3D barchart? Abortions in England and East Midlands What % of abortions at 13+ gestation in East Midlands?

Would we agree that, in this instance, a 3-D chart is an advantage? Do you have any alternative suggestions? Adapted from Age-class prevalence rates for selected conditions from the Health Survey for England, Self reported "very bad health” Asthana, S et al. J Epidemiol Community Health 2004;58: Copyright ©2004 BMJ Publishing Group Ltd. men women

Clustered and stacked bar charts are used to describe two or more categorical variables simultaneously. Clustered bar chart showing the percentage in each group within each gender. Stacked bar chart showing the number of people of each gender, within each of four groups. Group UnclassifiedNormalIGTNew Diabetes Percent Gender Male Female Group UnclassifiedNormalIGTNew Diabetes Count Gender Female Male

100% stacked vertical bar chart Difficult to make comparisons among the second, third, or subsequent segments in a stacked bar because judgment is not being made from a common base. Which region has largest proportion of males ?

The scarf chart is a special case of the stacked vertical bar. Comparisons are easier, but, where possible, avoid too many comparisons

Highlight the areas of interest

Coloured blobs and whiskers show a lot of information

Would it help to add numbers to your bars?

False origins should be marked

Presenting charts in juxtaposition: which is more powerful? Breast cancer incidence and mortality by deprivation South West

Or this? Breast cancer incidence and mortality by deprivation, South West

Lines or bars? Length of stay as an inpatient Count

Tobacco use and poverty: high prevalence among the world’s poorest

Combination of line and area graph show trend against target Source SWPHO

Not using a consistent scale leads to misrepresentation of trends.

Funnel plots – outliers must be named Notes: Population is adjusted due to standardisation calculations. SD = standard deviation Source: Cancer Registry data, South West Public Health Observatory; Populations, Office for National Statistics. Outliers above and below should be named. Age- stan dard ised rate per 100, 000 pop ulati on Dorchester Population Figure 2.6: Lung cancer incidence in males (age-standardised rate per 100,000) by Local Authority in the South West region, 2002–06 average

Scatter plot SWPHO report on rural deprivation 2001

Histogram with normal-curve and statistics for cholesterol measurements. useful for illustrating the shape of the distribution of a batch of numbers Histogram

Boxplots are graphical representations which clearly show the quartiles and extremes or outliers of a set of data in a compact manner. Median 1 st Quartile 3 rd Quartile Outliers “unusual observations” Minimum Maximum If you turn a histogram on its side you have a boxplot

Boxplots as used in Health Profiles 2007

Spidergram can compare several variables simultaneously

Does adding pictures make the graph more powerful?

Retrospective analysis of presumed Shipman victims How would you create this chart?

References Edwin R Tufte: the visual display of quantitative information, 2006 Graphics Press, Cheshire, Connecticut Gordon Blunt: The Good, the Bad and the ugly CACI Ltd