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# Statistics Done Wrong: The Woefully Complete Guide

by

Everyone knows that abuse of statistics is rampant in popular media. Politicians and marketers present shoddy evidence for dubious claims all the time. But smart people make mistakes too, and when it comes to statistics, plenty of otherwise great scientists--yes, even those published in peer-reviewed journals--are doing statistics wrong.

"Statistics Done Wrong" comes to the ...more

"Statistics Done Wrong" comes to the ...more

## Get A Copy

Paperback, 176 pages

Published
March 16th 2015
by No Starch Press
(first published April 27th 2013)

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It's a very well-writt ...more

Towards the end, the book veers a bit off course and get more into the ethics of research and research publication. It is interesting (but not really ne ...more

So who is this book for then? Everyone who works with statistics and/or data analytics, and wants to get a handle on some of the most common mistakes and fallac ...more

- "If you administer questions like this one [a typical question about base rate fallacy] to statistics students and scientific methodology instructors, more than a third fail. If you ask doctors, two thirds fail." Yikes

- "of the top-cited research articles in medicine, a quarter have gone untested a ...more

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**statistics assignment help**also. So, I am waiting. If one your tutors can help me, I will take regular classes since I want to score good grades during my exams. In case you aren’t able to assign a tutor recommend someone who can assist. ...more

1. Normal distribution

2. How to use p value with confidence intervals?

3. When to use p value?

4. How to tread between the fine line of using deceptive statistics vs reading the actual impact

A lot of strategies in the organisation is built seeing the co-related data but there is never an attempt to find the causation. This book highlights how we can do so with the examples in Pharma R&D industry.

Overall, it is a good read and a highly recommendable one. ...more

I consider myself reaso ...more

It's mostly stuff I think I already knew, but it was helpful to have it systematically and clearly presented.

The author is a CMU statistics grad student with a physics back ...more

The main value of this book I think are all the anecdotes of statistic ...more

ch2: confidence intervals offer more information than p-values and can be used to compare groups of different sizes. statistical power is very important, and underpowered studies might result in truth inflation. statistically insignificant does not mea ...more

Yes, people over-rely on and misinterpret p-values. Yes, people "double-dip" and torture/exhaust their data, hunt for statistically sig ...more

1. Statistics is easy to screw up.

2. Here are all the ways you can screw them up.

3. Here is the actual math that proves it's being screwed up.

#1 is absolute -- you cannot come away from this book without knowing that statistics is a messy science. I got about half of #2 -- I have a better idea of how statistics can be wrong. #3 is rough -- especially in the beginning, there's some math that was just lost on it.

But this is still a great book, because socie ...more

Topics include: type M error and the problem of underpowered statistics, pseudoreplication, the base rate fallacy, the problems with p values and why confidence intervals are so much better, double dipping data and when to stop a study, the problems wit ...more

In its own words, ‘it explains how to think about p values, significance, insignificance, confidence intervals, and regression’.

By the time you’ve finished, you’ll be able to spot a dodgy A/B test from a mile off! Since it’s geared towards a more academic audie ...more

Reinhart provides compelling evidence that a large portion of scientific research findings (or interpretations thereof) are probably bogus to some extent or another. In addition to providing numerous examples of the types of common st ...more

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“Misconceptions are like cockroaches: you have no idea where they came from, but they’re everywhere—often where you don’t expect them—and they’re impervious to nuclear weapons.”
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“The first principle is that you must not fool yourself, and you are the easiest person to fool. — Richard P. Feynman”
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