If you lived through the pandemic, you probably heard words like “R number,” “herd immunity,” “excess mortality,” and “statistical significance” more times than you can count. You were told to follow the science. But no one handed you the tools to understand what that actually meant.
This book is for:
Undergraduate students trying to make sense of public health and health statistics
Healthcare professionals, journalists, and policy analysts who work with medical research but were never taught how to interrogate it properly
Curious readers who felt confused, misled, or overwhelmed by shifting expert guidance
Early-career researchers who want the philosophical grounding their methods courses skipped
Bad Numbers is not a textbook. It is a detective story about how epidemiology really works.
Instead of dry definitions, you will follow real outbreaks, famous reversals, controversial studies, and the human beings behind the numbers. You will see how John Snow traced cholera to a water pump without knowing what a germ was. You will understand how researchers proved cigarettes cause lung cancer without running an experiment. You will discover why “doubled risk” can be both technically true and wildly misleading.
Along the way, you will learn how to:
Interpret relative risk and absolute risk without being manipulated
Understand case-control studies, cohort studies, and randomized trials in plain English
Spot confounding, healthy user bias, and statistical sleight of hand
Make sense of the R number and epidemic models
Evaluate screening programs and early detection claims
Read international health comparisons with a skeptical eye
Live comfortably with uncertainty rather than demanding false certainty
Epidemiology is not a collection of formulas. It is a way of thinking about populations, evidence, and probability. It is messy, powerful, limited, and often misunderstood.
By the end of this book, you will not just know what the numbers mean. You will know what questions to ask when someone presents them.
This is your guide to understanding medical research without a PhD, following public health debates without panic, and recognizing the difference between honest uncertainty and bad science.
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Paperback. Condición: new. Paperback. If you lived through the pandemic, you probably heard words like "R number," "herd immunity," "excess mortality," and "statistical significance" more times than you can count. You were told to follow the science. But no one handed you the tools to understand what that actually meant.This book is for: Undergraduate students trying to make sense of public health and health statisticsHealthcare professionals, journalists, and policy analysts who work with medical research but were never taught how to interrogate it properlyCurious readers who felt confused, misled, or overwhelmed by shifting expert guidanceEarly-career researchers who want the philosophical grounding their methods courses skippedBad Numbers is not a textbook. It is a detective story about how epidemiology really works.Instead of dry definitions, you will follow real outbreaks, famous reversals, controversial studies, and the human beings behind the numbers. You will see how John Snow traced cholera to a water pump without knowing what a germ was. You will understand how researchers proved cigarettes cause lung cancer without running an experiment. You will discover why "doubled risk" can be both technically true and wildly misleading.Along the way, you will learn how to: Interpret relative risk and absolute risk without being manipulatedUnderstand case-control studies, cohort studies, and randomized trials in plain EnglishSpot confounding, healthy user bias, and statistical sleight of handMake sense of the R number and epidemic modelsEvaluate screening programs and early detection claimsRead international health comparisons with a skeptical eyeLive comfortably with uncertainty rather than demanding false certaintyEpidemiology is not a collection of formulas. It is a way of thinking about populations, evidence, and probability. It is messy, powerful, limited, and often misunderstood.By the end of this book, you will not just know what the numbers mean. You will know what questions to ask when someone presents them.This is your guide to understanding medical research without a PhD, following public health debates without panic, and recognizing the difference between honest uncertainty and bad science. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9798249695668
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Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: L2-9798249695668
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Librería: CitiRetail, Stevenage, Reino Unido
Paperback. Condición: new. Paperback. If you lived through the pandemic, you probably heard words like "R number," "herd immunity," "excess mortality," and "statistical significance" more times than you can count. You were told to follow the science. But no one handed you the tools to understand what that actually meant.This book is for: Undergraduate students trying to make sense of public health and health statisticsHealthcare professionals, journalists, and policy analysts who work with medical research but were never taught how to interrogate it properlyCurious readers who felt confused, misled, or overwhelmed by shifting expert guidanceEarly-career researchers who want the philosophical grounding their methods courses skippedBad Numbers is not a textbook. It is a detective story about how epidemiology really works.Instead of dry definitions, you will follow real outbreaks, famous reversals, controversial studies, and the human beings behind the numbers. You will see how John Snow traced cholera to a water pump without knowing what a germ was. You will understand how researchers proved cigarettes cause lung cancer without running an experiment. You will discover why "doubled risk" can be both technically true and wildly misleading.Along the way, you will learn how to: Interpret relative risk and absolute risk without being manipulatedUnderstand case-control studies, cohort studies, and randomized trials in plain EnglishSpot confounding, healthy user bias, and statistical sleight of handMake sense of the R number and epidemic modelsEvaluate screening programs and early detection claimsRead international health comparisons with a skeptical eyeLive comfortably with uncertainty rather than demanding false certaintyEpidemiology is not a collection of formulas. It is a way of thinking about populations, evidence, and probability. It is messy, powerful, limited, and often misunderstood.By the end of this book, you will not just know what the numbers mean. You will know what questions to ask when someone presents them.This is your guide to understanding medical research without a PhD, following public health debates without panic, and recognizing the difference between honest uncertainty and bad science. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9798249695668
Cantidad disponible: 1 disponibles