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Stephanie Glen
  • Female
  • Jacksonville, FL
  • United States
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Profile Information

Short Bio:
Stephanie Glen is Editorial director at DataScienceCentral.com. She is a mathematician and statistician. After working for several years teaching mathematics and statistics at the university level, she created and developed the website StatisticsHowTo.com.
Company:
Andale Publishing, LLC
Job Title:
CEO
Seniority:
Executive
Job Function:
Other
Industry:
Mathematics Education
Interests:
Contributing

Stephanie Glen's Blog

What is Good Data and Where Do You Find It?

Posted on March 31, 2021 at 9:53am 0 Comments

  • Bad data is worse than no data at all.
  • What is “good” data and where do you find it?
  • Best practices for data analysis.

There’s no such thing as perfect data, but there are several factors that qualify data as good [1]:

  • It’s readable and well-documented,
  • It’s readily available. For example, it’s…
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Often Confused Terms in Statistics

Posted on March 24, 2021 at 1:54pm 1 Comment

  • Do you know the difference between a covariate and covariance, or probable and plausible?
  • Many terms in statistics are confused, even by experts
  • Eleven of the most commonly confused terms

Hundreds of years of statistical analysis by tens of thousands of independent researchers has led to an array of similar sounding…

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Data Science Lessons Learned from the Covid-19 Calamity

Posted on March 19, 2021 at 7:00am 0 Comments

  • Covid-19 data was haphazardly collected and analyzed, leading to a national disaster.
  • Pandemic predictions were no more accurate than a Magic 8 Ball.
  • Lessons to be learned from the mistakes made.

In the early days of the Covid-19 pandemic, the U.S. government didn’t have the faintest clue about the pandemic's…

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4 Tips to Improve Your Statistical Literacy

Posted on March 9, 2021 at 1:38pm 0 Comments

  • Improve your statistical literacy by following a few good practices.
  • A few examples of "unstatistics".
  • Four tips for avoiding common pitfalls in data analysis.

Statistical literacy (assessing statistical statements, arguments and associations) is extremely important for producing and interpreting results from data…

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At 3:52am on December 11, 2019, Jason Posavad said…

Your article is so relevant Stephanie, as I am 48 and contemplating an online masters in Data Science.  My answer has been to do as much as I can through MOOCs, self-driven projects, and other less-expensive learning.  If it gets to the point that I have done all of that and proven to myself that I can do Data Science, and that I need a degree to get land a job, I will then do it.   Reality is you do need to be more careful and more risk-averse as you age, as the time to recover from mistakes is just not there anymore.  

 
 
 

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