What do statisticians research?

A dive into a statistical analysis on... statistics?

Stay updated with the channel and some stuff I make!

[qwerty]

He hasn't done a map on statistics yet?!

[John-qohw]

Wow, you helped me get rid of a lot of the black box I had in my mind when I heard the word statistics. Thank you.

[marcbollee]

Super interesting! I'd love to see a video about some of the more obscure topics you mentioned. Very high quality content, thank you!

[mx]

I’m a community college student soon going to a larger university and will be majoring in statistics (and potentially biostatistics as I want to have a positive impact in the space). I just want to say I love your videos and your ability to foster intuition. A true goldmine, thank you!

p.s. If you have any advice for the path of a thoughtful and strong statistician/biostatistician I’d be grateful

[sanketkhatavkar]

Thank you for thoroughly deep diving into stats and presenting to us these interesting informational topics.

[TheMegaDTGT]

Hey man. Thank You for this video. I’m planning on doing the PhD in stat so this will be very helpful 🤗

It’s funny as for me the Graphical Models are the most interesting part of statistics. I’m working in this subfield for over a year now haha

[twentytwentyeight]

When you said “we’re using statistics to explain statistics”, I instantly subbed to ❤ wish I’d found you sooner (shakes fist vigorously at yt algo)

[illbeback]

Refreshing to see a video that mentions clustering and dynamic clustering in the era of the holy GPT. Back in the day (3 years ago) I was implementing Dynamic Topic Models (David Blei) in uni, and this made me nostalgic!

[programmingwithian]

I'm taking a class on Time Series Analysis next semester. Quite excited for it!

[YuweiCheng-yyuk]

Really enjoy all your videos. Very unique educational channel on statistics. Keep uploading!

[Kram]

Graphs (in the sense of graphical models) are hugely important as they basically can capture any type of pairwise relationship you might want. Specializing to specific types of graphs you can capture decision trees, causal orders, processes, various topological constraints, or many other notions of interest. And nearly anything can be framed in terms of graphs.
So it's no wonder that's a huge area in statistics.
(There are extensions that allow you to capture higher order relationships that consider three or more objects at a time. Multi graphs, hypergraphs, Abstract Simplical Complexes, Simplical Sets (different generalizations of graphs). But you can get really really far before you actually need those. Almost anything can be captured with just pairwise relationships)

[matteogirelli]

I've studied in Bologna and confirm that it's a very good uni, especially in stats and applied stats

[tamirmashbat]

Stunned by what my Statistics is from what i've learned so far

[samuelm]

Cool!
Time series was most of my advanced econometrics class, so I was surprised to hear that in other fields it's not as big a deal. But that makes sense I guess.

[kristianwichmann]

The article seems like a nice review of a lot of "classical" NLP methods. Clearly pre-LLM-revolution.

[BorrWick]

Why wouldn't they use a probabilistic topic model. Blei et al 2006 Dynamic Topic Models would be a perfect fit for the task

[brandonheaton]

Hanging around biostatisticians, surely you have heard of Neo4J and knowledge graphs. Graphs (vertices and edges) are used to represent protein/protein interactions or metabolic pathways and their interconnections. They can also represent other levels of interaction, say cells in an organism or species in an ecosystem

[pichirisu]

Would you please consider doing a video going over the the amount/type/etc. of coding that is required by statisticians? I'd love to be a statistician and am doing undergrad for it atm with basic statistical packages which is totally fine and a lot of fun, but if I have to get more into data science-type work then I'm absolutely checked out cause that kind of coding instantly bores me. It would be highly appreciated, thanks.

[MusicEngineeer]

I think I recognize this cosine distance as something like "one minus correlation" or "one minus covariance" or something like that. Right? ...and I guess that it never gets negative is only because the x_i, y_i are constrained to be positive?

[riccardopucci]

Me watching my professors appear on screen all of a sudden 👁👄👁