ASA-CRC series on statistical reasoning in science and society
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
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Includes bibliographical references and index.
CONTENTS NOTE
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Why visualise? -- Translating numbers to images -- Continuous and discrete numbers -- Percentages and risks -- Showing data or statistics -- Differences, ratios, correlations -- Visual perception and the brain -- Showing uncertainty -- Time trends -- Statistical predictive models -- Machine learning techniques -- Many variables -- Maps and networks -- Interactivity -- Big data -- Visualisation as part of a bigger package -- Some overarching ideas.
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SUMMARY OR ABSTRACT
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This is the age of data. There are more innovations and more opportunities for interesting work with data than ever before, but there is also an overwhelming amount of quantitative information being published every day. Data visualisation has become big business, because communication is the difference between success and failure, no matter how clever the analysis may have been. The ability to visualize data is now a skill in demand across business, government, NGOs and academia.