Introducing my statistics/data science blog - forthcoming posts and call for feedback

2년 전

For many years I have worked as a statistics lecturer but done statistical consulting on the side. Recently I decided to start my own company and do consulting, together with statistics training and eventually some online courses, full-time.

The utopian-io platform seems like a good space for me to blog about statistics/data science and also test some of my training material and ideas. Here are a few ideas that I have had for future blog posts:

  • What is data science and how does it differ from statistics? Whilst the distinction may not seem important, it can be crucial when you are looking to recruit a particular skill-set.
  • Reporting and documenting 101 - how to correctly report your analysis (this is at the forefront of my mind having just inherited an analysis project where the reporting and documenting has not been well done.
  • Examples of where bad statistics has lead to bad decision making.
  • Why false positives (and true negatives) are so important to consider in the age of machine learning.
  • Guides to the R statistics software - I have used R for 21 years and it is my go to tool for statistical analysis.
  • Technical analysis - how to read candlestick charts and other crypto/stock trading tools.
  • Bias, sample, and data collection - how to avoid pitfalls and spot dubious data.

Are you interested in learning more about statistics/data science? What kind of content would most interest you?

I would welcome any feedback on the topics above and any other topics that you might be interested in (whether they are philosophical or technical, broad or specific).

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Hello Colleague! I'm working in chemometrics or statistics in chemistry.
"How to lie with statistics" is always popular
"How to do bad statistics", I see it every day (applying the tests that require larger datasets or data that don't have certain distribution)

Also, statistics for dummies, starting from what's the difference between median and average, what is histogram and what does sigma means.

Good luck!


Those fundamentals/basics are definitely always good to go over.


It's never easy to balance the blog. It would be probably good to have two sections, "for dummies" to attract some traffic and "for experts" with hardcore advanced ideas so you can show the level of excellence.

Its great to see that you are doing a data science, lets get the data from Steem Blockchain and try to find out something using the data itself. For example, lets create an fun filled experiment where the data is with everyone (steem data or utopian or blog or any other tag data), and given a task where you find out some statistics or analysis.


I like this although last time I checked steemsql was charging to get data. Do you know of a free alternative?


I knew, but I guess the project is abandoned. Though 1 SBD a day will be fine for SteemSQL if not monthly.

Oh that would be really nice. I would love to learn the statistics from inside out. I mean I use it everyday, while analyzing data of my experiments. But I would like to have a better understanding of it. Like what distribution does my data fall in. What is optimal N size for a given effect size. What statistical test to use. Esp in regards to biological experiments. Like what is the right way to analyze fold changes in geneexpression. Or how do you go about analyzing data which has variation in basal expression of some gene but the treatment causes an increase in either case. You know. I would be interested in that kind of things for sure.


All very good questions! I definitely see people using stats in their disciplines who get taught a very recipe driven approach - which is fine for simple scenarios where you can just follow the recipe - but without that understanding they can get themselves into trouble if the recipe doesn't fit the problem (like putting the green salad in the oven for an hour because you only got taught baking recipes).

following as I'm a baby Data Scientist

Hello there!

I can't help but notice that you used the Utopian-io tag on a blog post that is entirely unrelated to open source software. That's an inappropriate way to use our tags, I'm afraid.

If you want to contribute content that is relevant to Utopian, please read our guidelines. I would also recommend reading our weekly Top Of Utopian posts to get an idea of the kind of content we particularly like.

I look forward to seeing awesome relevant content from you in the future.

Due to ineligibility, your contribution has not been evaluated.

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Apologies. I was going to say more about the R Software which is open source.

i would like to learn about stats . would be happy to read your next blog post . and will prefer follow you for updates :)

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Following right away! Just saw this post from my GINAbot feed.

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