Stephanie Glen
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  • Jacksonville, FL
  • United States
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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.
Andale Publishing, LLC
Job Title:
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Mathematics Education

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…

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…


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…


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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