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Re: Statistical analysis

Subject: Re: Statistical analysis
From: "Peter Neilson" <neilson -at- windstream -dot- net>
To: techwr-l -at- lists -dot- techwr-l -dot- com
Date: Mon, 11 Apr 2016 09:50:53 -0400

While we are caveatating...
- Fallacy of assigning causes to the observed coincidences (false correlation).
- Sample size problems even when it looks like there aren't any.
- Lumping incommensurables together to create a decently sized sample set.
- Selection of data by unidentified causes.

In some agenda-driven studies (for instance, funded to provide a particular result) outliers or data that is "obviously bad" are eliminated. This has the result of sharpening a peak (reducing standard deviation), or even creating a peak where none previously existed. In extreme cases researchers might ignore a bimodal distribution. Fortunately we are all too smart to fall into any of those blunders.

On Mon, 11 Apr 2016 09:20:18 -0400, Dan Goldstein <DGoldstein -at- nuot -dot- com> wrote:

That's correct, and it should be mentioned in the Limitations section. However, it should also be noted the study compares the TECHWR-L posts with a number of published studies on gender and communication. Those studies treat gender as binary.

-----Original Message-----
From: Gleb Dolgich
Sent: Monday, April 11, 2016 9:07 AM
To: Dan Goldstein
Cc: TECHWR-L (techwr-l -at- lists -dot- techwr-l -dot- com)
Subject: Re: Statistical analysis

Another caveat is that gender can be non-binary.

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Follow-Ups:

References:
Statistical analysis: From: Dan Goldstein
RE: Statistical analysis: From: Doug Grossman
RE: Statistical analysis: From: Dan Goldstein
RE: Statistical analysis: From: Doug Grossman
RE: Statistical analysis: From: Dan Goldstein
Re: Statistical analysis: From: Gleb Dolgich
RE: Statistical analysis: From: Dan Goldstein

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