Examine and solve the common misconceptions and fallacies that non-statisticians bring to their
interpretation of statistical results. Explore the many pitfalls that non-statisticians-and
also statisticians who present statistical reports to non-statisticians-must avoid if
statistical results are to be correctly used for evidence-based business decision making.
Victoria Cox senior statistician at the United Kingdom's Defence Science and Technology
Laboratory (Dstl) distills the lessons of her long experience presenting the actionable
results of complex statistical studies to users of widely varying statistical sophistication
across many disciplines: from scientists engineers analysts and information technologists to
executives military personnel project managers and officials across UK government
departments industry academia and international partners. The author shows how faulty
statistical reasoning often undermines the utility of statistical results even among those with
advanced technical training. Translating Statistics teaches statistically naive readers enough
about statistical questions methods models assumptions and statements that they will be
able to extract the practical message from statistical reports and better constrain what
conclusions cannot be made from the results. To non-statisticians with some statistical
training this book offers brush-ups reminders and tips for the proper use of statistics and
solutions to common errors. To fellow statisticians the author demonstrates how to present
statistical output to non-statisticians to ensure that the statistical results are correctly
understood and properly applied to real-world tasks and decisions. The book avoids algebra and
proofs but it does supply code written in R for those readers who are motivated to work out
examples. Pointing along the way to instructive examples of statistics gone awry Translating
Statistics walksreaders through the typical course of a statistical study progressing from the
experimental design stage through the data collection process exploratory data analysis
descriptive statistics uncertainty hypothesis testing statistical modelling and multivariate
methods to graphs suitable for final presentation. The steady focus throughout the book is on
how to turn the mathematical artefacts and specialist jargon that are second nature to
statisticians into plain English for corporate customers and stakeholders. The final chapter
neatly summarizes the book's lessons and insights for accurately communicating statistical
reports to the non-statisticians who commission and act on them. What You'll Learn Recognize
and avoid common errors and misconceptions that cause statistical studies to be misinterpreted
and misused by non-statisticians in organizational settings Gain a practical understanding of
the methods processes capabilities and caveats of statistical studies to improve the
application of statistical data to business decisions See how to code statistical solutions in
R Who This Book Is For Non-statisticians-including both those with and without an introductory
statistics course under their belts-who consume statistical reports in organizational settings
and statisticians who seek guidance for reporting statistical studies to non-statisticians in
ways that will be accurately understood and will inform sound business and technical decisions
