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Stephanie Glen's Page
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
Clearing up the Covid-19 Test Accuracy Debate with Data Science
Posted on January 25, 2021 at 4:30pm 0 Comments 0 Likes
- A negative Covid-19 test result had very little meaning in 2020.
- A new tool allows you to better interpret the meaning of a negative test result.
- I used the tool to find the probability that my October Covid-19 negative test result was accurate.
This useful, user-friendly tool is a great example of data science at work.…
4 Common Data Analysis Mistakes to Watch Out For
Posted on January 19, 2021 at 8:16am 0 Comments 0 Likes
- Statistical analysis is poorly misunderstood by many, resulting in array of problems.
- There are many ways to ruin your data analysis.
- 4 of the less well-known mistakes to watch out for.
I recently came across an article in eLife (a peer reviewed journal) called Ten common statistical mistakes to watch out for when writing or reviewing a manuscript [1]. Although the paper was geared towards reviewers of research papers, many of the…
ContinueGenerative vs. Discriminative Models in One Picture
Posted on January 11, 2021 at 11:39am 0 Comments 0 Likes
- Discriminative and generative models have distinct differences,
- Discriminative methods are simpler but not necessarily better,
- This One Picture outlines a few major differences between the methods, along with a few examples and use cases.
Read any textbook on the difference between generative and discriminative models and…
Fraudulent Covid-19 Data and Benford's Law
Posted on December 31, 2020 at 4:33am 0 Comments 0 Likes
An interesting application of Benford's and Zipf's Laws to fraudulent Covid-19 data was published…
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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.