statisticsdonewrong.com

Welcome — Statistics Done Wrong

The woefully complete guide. If you’re a practicing scientist, you probably use statistics to analyze your data. From basic. Tests and standard error calculations to Cox proportional hazards models and propensity score matching, we rely on statistics to give answers to scientific problems. This is unfortunate, because most of us don’t know how to do statistics. Assumes no prior knowledge of statistics, so you can read it before your first statistics course or after thirty years of scientific practice.

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Welcome — Statistics Done Wrong | statisticsdonewrong.com Reviews

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The woefully complete guide. If you’re a practicing scientist, you probably use statistics to analyze your data. From basic. Tests and standard error calculations to Cox proportional hazards models and propensity score matching, we rely on statistics to give answers to scientific problems. This is unfortunate, because most of us don’t know how to do statistics. Assumes no prior knowledge of statistics, so you can read it before your first statistics course or after thirty years of scientific practice.

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1 statistics done wrong

2 alex reinhart

3 contact me

4 contents

5 introduction

6 changes

7 acknowledgements

8 copyright note

9 the power of

10 values

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Welcome — Statistics Done Wrong | statisticsdonewrong.com Reviews

https://statisticsdonewrong.com

The woefully complete guide. If you’re a practicing scientist, you probably use statistics to analyze your data. From basic. Tests and standard error calculations to Cox proportional hazards models and propensity score matching, we rely on statistics to give answers to scientific problems. This is unfortunate, because most of us don’t know how to do statistics. Assumes no prior knowledge of statistics, so you can read it before your first statistics course or after thirty years of scientific practice.

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statisticsdonewrong.com

1

Bibliography — Statistics Done Wrong

http://www.statisticsdonewrong.com/zbibliography.html

Deriving chemosensitivity from cell lines: Forensic bioinformatics and reproducible research in high-throughput biology. The Annals of Applied Statistics. The (mis)reporting of statistical results in psychology journals. Stopping Randomized Trials Early for Benefit and Estimation of Treatment Effects: Systematic Review and Meta-regression Analysis. Statistical Power of Negative Randomized Controlled Trials Presented at American Society for Clinical Oncology Annual Meetings. Journal of Clinical Oncology.

2

An introduction to data analysis — Statistics Done Wrong

http://www.statisticsdonewrong.com/data-analysis.html

An introduction to data analysis. Much of experimental science comes down to measuring changes. Does one medicine work better than another? Do cells with one version of a gene synthesize more of an enzyme than cells with another version? Does one kind of signal processing algorithm detect pulsars better than another? Is one catalyst more effective at speeding a chemical reaction than another? Statistics provides the answer. If we know the. That’s a bit tricky, so read it again. Intuitively, we can see ho...

3

Index — Statistics Done Wrong

http://www.statisticsdonewrong.com/genindex.html

Right turn on red. Right turn on red. The revised and expanded. With three times as many statistical errors and examples, is available in print and eBook! An essential book for any scientist, data scientist, or statistician. An introduction to data analysis. Statistical power and underpowered statistics. Pseudoreplication: choose your data wisely. Value and the base rate fallacy. When differences in significance aren’t significant differences. Stopping rules and regression to the mean. What can be done?

4

Statistical power and underpowered statistics — Statistics Done Wrong

http://www.statisticsdonewrong.com/power.html

Statistical power and underpowered statistics. We’ve seen that it’s possible to miss a real effect simply by not taking enough data. In most cases, this is a problem: we might miss a viable medicine or fail to notice an important side-effect. How do we know how much data to collect? You can’t just flip the coin a hundred times and count the heads. Even with a perfectly fair coin, you don’t always get fifty heads:. Let’s work out the math. Let’s say we look for a. This is called a. Along the horizontal ax...

5

Welcome — Statistics Done Wrong

http://www.statisticsdonewrong.com/index.html

The woefully complete guide. If you’re a practicing scientist, you probably use statistics to analyze your data. From basic. Tests and standard error calculations to Cox proportional hazards models and propensity score matching, we rely on statistics to give answers to scientific problems. This is unfortunate, because statistical errors are rife. Assumes no prior knowledge of statistics, so you can read it before your first statistics course or after thirty years of scientific practice. The base rate fal...

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Tough Love and Kittens. They're not mad, just disappointed. The TL&K Philosophy. Downloads & Things We Like. Never Sucked Dick For Coke, But Food Addiction Is Real, I Seen It. 3 Realizations One Comes To When Getting Less Fat. THERE’S A MIRACLE PILL! High Protein Sugar-Free Jello. The thing they don’t tell you about getting lean. Subscribe to our Newsletter! Author: Lincoln (not a doctor). High Protein Sugar-Free Jello. I’m working on a DIY version with gelatin that can be made in bulk. 3/4 cup cold water.

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Sometimes i try to write them down. Saturday, March 29, 2014. I managed to avoid playing it most of the week, but I still had time to hone my strategy even more! I actually got kind of close to 8192. Anyway.I'm not allowed to play again until the rough draft for my paper is done next week. Friday, March 28, 2014. Carbon Metrics for Investors. Interest in measuring the GHG footprint and the GHG intensity of investment portfolios is growing! Presents a good overview of these different metrics. An individua...

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ML and Statistics done wrong. Today I came up with a recent article. From Cheng-Tao Chu, Director of Analytics at Codecademy about 7 common mistakes in applying Machine Learning and was happy to find that at least some of the mistakes that I've done in the past are common :). On the other hand, in the author's blog I found a reference to another resource: Statistics done wrong. List of the more egregious statistical fallacies regularly committed in the name of science. Proudly published with Ghost.

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Java web components, controls and JSP custom tags. Saturday, May 30, 2015. 27 free Data Mining books. We would like one more: Statistics Done Wrong. See here more free Data Science books. Posted by Coldbeans software. Subscribe to: Post Comments (Atom). View my complete profile. Foursquare tips and forums. Twitter buy vs. sell. Tweet vs. Tweet. Geo-location for Telecom Operators. Powered by Google Analytics. Simple template. Powered by Blogger.

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Cap'n Refsmmat's Blog. Just another SFN Blogs site. Statistics Done Wrong: How scientists abuse statistics. July 31, 2012. Middot; 4 Comments. Statistical results are everywhere in science. When the Higgs boson discovery was announced, nearly every news article mentioned how there was just a one in 1.74 million chance that the results were a statistical fluke. Well, that’s not entirely true: some said one in 5 million, others one in 2 million, others one in a million. All of them were wrong. After all, w...

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A random walk through a subset of things I care about. Science, math, computing, higher education, open source software, economics, food etc. Thursday, May 28, 2015. This is truly awesome! The Big History Project is a joint effort between teachers, scholars, scientists, and their supporters to bring a multi-disciplinary approach to knowledge to lifelong learners around the world. Posted by Sachin Shanbhag. Links to this post. Tuesday, May 26, 2015. Consistency" Bug in NumPy? Import numpy as np. Finally, ...

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Welcome — Statistics Done Wrong

The woefully complete guide. If you’re a practicing scientist, you probably use statistics to analyze your data. From basic. Tests and standard error calculations to Cox proportional hazards models and propensity score matching, we rely on statistics to give answers to scientific problems. This is unfortunate, because most of us don’t know how to do statistics. Assumes no prior knowledge of statistics, so you can read it before your first statistics course or after thirty years of scientific practice.

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