Bad Data: How Governments, Politicians And The Rest Of Us Get Misled By Numbers

In Bad Data, Real-World Stories And Policy Moments Illuminate How Data Is Collected, Interpreted, And Sometimes Misinterpreted. The Book Dives Into Cases That Feel Almost Like A Data Detective Story—Such As A Hungarian Businessman's Bright Idea That Left Hundreds Of Thousands Unaccounted For In Uk Migration Statistics—Showing How Numbers Can Drift, Be Revised, Or Be Read In Competing Ways. It Also Explores Debates Over Poverty Trends, Where The Same Official Figures Can Lead To Two Different Conclusions Depending On Definitions And Timing. Through These Cases, Bad Data Sheds Light On The Human Processes Behind Numbers And The Consequences Of Shaky Data For Policy.

Written In A Warm, Reader-Friendly Voice, The Book Blends Storytelling With Clear Explanations Of Data Provenance, Uncertainty, And Measurement. It Makes Learning Feel Accessible And Engaging By Illustrating Concepts With Concrete Examples, Pacing The Material To Mirror How Data Is Collected, Revised, And Interpreted In The Real World. Whether You’Re New To Statistics Or Already Comfortable With Numbers, This Book Helps You See The Structure Of Data, The Risks Of Misinterpretation, And The Importance Of Asking The Right Questions Before Drawing Conclusions.

• Real-World Case Studies That Demonstrate Data Pitfalls And Their Policy Consequences
• Clear Explanations Of Data Quality, Sources, Uncertainty, And Measurement
• Strategies For Reading Statistics Critically And Evaluating Trustworthiness
• Engaging, Narrative-Driven Presentation That Makes Complex Ideas Accessible

After Finishing Bad Data, Readers Will Feel Equipped To Scrutinize Statistics In The News And In Policy Debates, To Question Assumptions, And To Participate More Thoughtfully In Civic Conversations. The Book Leaves You With A Clearer Sense Of How Numbers Should Inform—Not Dictate—Our Decisions, And With A Confident, Hopeful Mindset About Engaging With Data In Everyday Life.