Principles of Applied Statistics 1st Edition by D. R. Cox (PDF)

Description

Applied statistics is more than data analysis, but it is easy to lose sight of the big picture. David Cox and Christl Donnelly distil decades of scientific experience into usable principles for the successful application of statistics, showing how good statistical strategy shapes every stage of an investigation. As you advance from research or policy question, to study design, through modelling and interpretation, and finally to meaningful conclusions, this book will be a valuable guide. Over a hundred illustrations from a wide variety of real applications make the conceptual points concrete, illuminating your path and deepening your understanding. This book is essential reading for anyone who makes extensive use of statistical methods in their work.

User’s Reviews

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐Wow. I’ve been a practitioner and professor for 20 years in stats, biostats and epidemiology. This book really crystallizes much of what I’ve picked up over the years. What a great refresher on so many topics. It is packed with knowledge. So packed that it might not work so well for someone getting this info for the first time. But for someone who has coursework and experience and looking for further insight, I highly recommend it.Gregory Zimmerman, Professor of Biology Lake Superior State University

⭐This book was definitely helpful and very clear instructionally. It was able to narrow down some pretty complex topics into much easier to understand versions.

⭐This is the book I was looking for. I am using it to teach to Doctoral level. I have advised my students to buy it from Amazon. fast deliver. Dr. DeLeon, Epidemiologist. Guatemala.

⭐Equations embedded in text are unreadable and cannot be zoomed in on.

⭐I checked this out from my university library. If you already understand the material then it is probably a good book to have as a refresher or to go over details issues. However, it is dense and formatted in a confusing manner. The text is broken up with numerous grey boxes with ‘illustration’ which, unfortunately, don’t always elucidate the topic being discussed. One gets the sense that the authors are writing for people at their own level of understanding, which given their pedigree, makes this an absurd choice for anyone who isn’t a seasoned statistician. I had hoped it might shed light but in truth it has only confused me or made me throw my hands up in confusion. There are a few parts that are helfpful for the applied statistician without Cox’s brilliance, but they are few. In short, it doesn’t come off as a ‘principled of’ book, more like a technical manual for experts already fluent in the arcane and complex descriptions used.

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