Correlation Coefficients in Data Science and Machine Learning (in One Picture)
In my first post on correlation coefficients, I outlined the differences between five popular coefficients: Pearson's,…See More
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Correlation Coefficients in Data Science and Machine Learning (in One Picture)
In my first post on correlation coefficients, I outlined the differences between five popular coefficients: Pearson's,…See More
Stumped by Bayes' Theorem? Try This Simple Workaround
Bayes' Theorem formula.Bayes' Theorem, which The Stanford Encyclopedia of Philosophy calls "...a simple mathematical formula" can be surprisingly difficult to actually solve. If you struggle with Bayesian logic, solving the "simple" formula involves not much more than…See More
"Coursera is the best platform from Johns Hopkins University
Some of them are simpler than it would be expected but they are really good :)
regards,"
MicroMasters: The Fast Way to Get Into Data Science
If the prospect of earning a masters degree in data science sounds too daunting (and expensive), then a MicroMasters might be a good fit for you. A MicroMasters is a "mini" masters degree, typically comprised of four courses. The courses are offered at a fraction of the cost of a typical masters program (around a tenth of the cost), so are a great way to wet your feet and see if data science is right for you.I'm actually enrolled in the MIT MicroMasters program right now. So far, I'm…See More
"Very interesting, thanks for sharing."
Model Fitting Tests You've Probably Never Heard Of (In One Picture)
When choosing a statistical test, you generally want to go for one of the more well-known ones, like the chi-square goodness of fit test.That's because more people are going to be able to understand your results, and you have the backing of a slew of…See More
Model Fitting Tests You've Probably Never Heard Of (In One Picture)
When choosing a statistical test, you generally want to go for one of the more well-known ones, like the chi-square goodness of fit test.That's because more people are going to be able to understand your results, and you have the backing of a slew of…See More
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- Company:
- Andale Publishing, LLC
- Job Title:
- CEO
- Seniority:
- Executive
- Job Function:
- Other
- Industry:
- Mathematics Education
- 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.
- Interests:
- Contributing
Stephanie Glen's Blog
Correlation Coefficients in Data Science and Machine Learning (in One Picture)
Posted on September 25, 2020 at 10:00am 0 Comments 0 Likes
In my first post on correlation coefficients, I outlined the differences between five popular coefficients: Pearson's,…
ContinueStumped by Bayes' Theorem? Try This Simple Workaround
Posted on September 15, 2020 at 11:29am 0 Comments 1 Like
Bayes' Theorem, which The Stanford Encyclopedia of Philosophy calls "...a simple mathematical formula" can be surprisingly difficult to actually solve. If you struggle with Bayesian logic, solving the "simple"…
ContinueMicroMasters: The Fast Way to Get Into Data Science
Posted on September 9, 2020 at 8:30am 1 Comment 0 Likes
If the prospect of earning a masters degree in data science sounds too daunting (and expensive), then a MicroMasters might be a good fit for you. A MicroMasters is a "mini" masters degree, typically comprised of four courses. The courses are offered at a fraction of the cost of a typical masters program (around a tenth of the cost), so are a great way to wet your feet and see if data science is right for you.
I'm actually enrolled in the MIT MicroMasters program…
ContinueModel Fitting Tests You've Probably Never Heard Of (In One Picture)
Posted on August 31, 2020 at 6:30am 0 Comments 1 Like
When choosing a statistical test, you generally want to go for one of the more well-known ones, like the chi-square goodness of fit test.That's because more people are going to be able to understand your results, and you have the backing of a slew of…
ContinueComment Wall (1 comment)
- 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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