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Stephanie Glen
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  • Jacksonville, FL
  • United States
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Latest Activity

Kiran liked Stephanie Glen's blog post Lognormal, Weibull, and Gamma distribution in One Picture
17 hours ago
Stephanie Glen's 2 blog posts were featured
yesterday
Selcuk Disci liked Stephanie Glen's blog post Statistical Uncertainty: Why are Covid-19 Figures so Varied?
Wednesday
Paul Bremner liked Stephanie Glen's blog post Statistical Uncertainty: Why are Covid-19 Figures so Varied?
Monday
Patrick Stroh commented on Stephanie Glen's blog post Understanding Covid-19 Statistics (in plain English)
"Left censored.  We are only seeing the worst cases (only the very ill).  So the various rates can be misleading until widespread testing (even of "healthy people")."
Monday
Patrick Stroh commented on Stephanie Glen's blog post Statistical Uncertainty: Why are Covid-19 Figures so Varied?
"All good points.  The left censoring of new cases seems particularly problematic."
Monday
Jay Magodia liked Stephanie Glen's blog post Statistical Uncertainty: Why are Covid-19 Figures so Varied?
Mar 22
Stephanie Glen's blog post was featured

Statistical Uncertainty: Why are Covid-19 Figures so Varied?

If you've been keeping up on the statistics for Covid-19 in the last week (and who hasn't?), you've probably noticed a wide variety of projections for deaths in the United States, ranging from the "best-case" scenario  (327 people) to the "doomsday" figure (2.2 million). Recent statistics published include:327 to 1.6 million (Former Former CDC director Tom Frieden, cited in the…See More
Mar 21
Paul Bremner commented on Stephanie Glen's blog post Understanding Covid-19 Statistics (in plain English)
""Generally, humans are immuned after infection by all of the "common cold" Coronovirii (I think there are 4?) for 6 to 9 months. That's why you get it every winter."   That's probably true of some viruses but…"
Mar 20
Lance Norskog commented on Stephanie Glen's blog post Understanding Covid-19 Statistics (in plain English)
"Generally, humans are immuned after infection by all of the "common cold" Coronovirii (I think there are 4?) for 6 to 9 months. That's why you get it every winter. So, we're looking at yearly meltdowns like this until…"
Mar 20
Stephanie Glen commented on Stephanie Glen's blog post Understanding Covid-19 Statistics (in plain English)
"Thanks, Paul. I'm going to look at modeling a little more in depth. I agree that common sense sometimes goes out of the window when it comes to statistics. Sometimes people just get lost in the data and alienate themselves from the real world."
Mar 20
Amit Dubey liked Stephanie Glen's blog post Understanding Covid-19 Statistics (in plain English)
Mar 20
Boujema Khemmich liked Stephanie Glen's blog post Best Resources to Learn Statistics (for Free!)
Mar 19
Paul Bremner liked Stephanie Glen's blog post Understanding Covid-19 Statistics (in plain English)
Mar 18
Paul Bremner commented on Stephanie Glen's blog post Understanding Covid-19 Statistics (in plain English)
"Good write-up and interesting references to the COVID-19 problem. It might be worth doing a similar analysis of the use of statistics (specifically forecasting/modeling) as it relates to COVID-19.  From what I can see, the UK Imperial college…"
Mar 18
Lava Kafle liked Stephanie Glen's blog post Understanding Covid-19 Statistics (in plain English)
Mar 17

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.
Field of Expertise
Other
Professional Status
Executive
Years of Experience:
14
Your Company:
Andale Publishing, LLC
Industry:
Mathematics Education
Your Job Title:
CEO
Interests:
Contributing

Stephanie Glen's Blog

Lognormal, Weibull, and Gamma distribution in One Picture

Posted on March 27, 2020 at 7:41am 0 Comments

At first glance, the Lognormal, Weibull, and Gamma distributions distributions look quite similar to each other. Selecting between the three models is "quite difficult" (Siswadi & Quesenberry) and the problem of testing which distribution is the best fit for data has been studied by a multitude of researchers.

If all the models fit the data fairly…

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Statistical Uncertainty: Why are Covid-19 Figures so Varied?

Posted on March 21, 2020 at 8:10am 1 Comment

If you've been keeping up on the statistics for Covid-19 in the last week (and who hasn't?), you've probably noticed a wide variety of projections for deaths in the United States, ranging from the "best-case" scenario  (327 people) to the "doomsday" figure (2.2 million). Recent statistics published include:

  • 327 to 1.6 million (Former Former CDC director Tom Frieden, cited in the…
Continue

Understanding Covid-19 Statistics (in plain English)

Posted on March 17, 2020 at 6:30am 5 Comments

My original intent with this article was to write about how to understand statistics in general. However, with the global pandemic on everyone's minds right now, it seems blithe to write an article on understanding statistics without a nod to current events. If you're uncomfortable or unfamiliar with statistics, you might find the facts and figures surrounding Covid-19 hard to decipher. Let's break down the key statistics into plain English and shed a little light on a few…

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Different Probability Distributions in One Picture

Posted on February 29, 2020 at 3:00pm 0 Comments

Data science uses many different probability distributions, but some are used more than others. This one picture shows an overview of five probability distributions data scientists will  find the most useful. See below the image for more information about the distributions.

Further Information:…

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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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