Відео

Excellent, had to search through several videos before landing on yours. A very clear and concise explanation on partial correlations.

Thanks Matthew for ShareThis

thanks a lot

this video is incredible, thank you so much!

this is really helpful. thank you so much!

very good explanation!

Thank you so much, an example on the last part "Working with time series" would be very useful.

can I find somewhere examples of random coefficient models where the variable of the random coefficient is not continuous but categorical? ideally written with STATA or SPSS?

Can you please explain why time series are not allowed? This would make the residuals non-independent of one another, but why does this invalidate the test? Would a LMM work better in this case, and if so would “time” as the continuous independent variable be the random effect to account for resampling of the same system? Thank you!

OMG, thank you so much for this very informative video, it really helped me a lot!

Super simplified, very help. Thank you!

Are LMM and LMEM the same thing?

Where does the observed difference at ~6:00 come from?

Thank you for making this video it really clarified the concepts for me

It's remarkable how inept professors are at explaining the simplest of concepts. You have surpassed most of mine, thank you very much.

I truly enjoy watching this tutorial. Thank you

Thank you very much! This helped me quite a lot!!

Is that Dr. Bob D pointing at the outcrop.

Thank you sir, it was very well explained.

Excellent work

6:45

You state "Dune size scales with flow depth; ripples scale with grain size instead". There are what are known as mega-flood ripples (such as the Camas Prairie ripples). These are over 30 feet high. Were they scaled up as a result of grain particle size? Or flow depth? Surely they scaled up in size due to flow depth.

Oh my goodness, thankyou for making a video that actually explains statistical content clearly! If I had a dollar for every video with a title like, "such and such analysis method, CLEARLY EXPLAINED!" then goes on to dive into the most complex content imaginable without proper explanation I'd be a very rich man. Sorry about this vent, I'm just very appreciative. Keep up the good work.

at 3:18, shouldn't it be Yt and Yt-1 rather than x?

This story seems straight forward - yet, after 8 minutes I still am clueless as where it is going to lead. Maybe it is just me, but when I need to learn something, I don't want a long tension arc: Oh, what is going to happen next... I want to start with a great picture of what is going to happen, and then fill in the details one after another, so I can sit and marvel, how the big initial problem step by step dissolves into smaller and understandable pieces. Inversing the story, starting from the conclusion, going to the basics also allows to stop once you understood enough.

Really clear. Thanks!

Fantastic video! Thank you so much! You are the best!

best!

Excellent. Thank you

very helpful, thank you!

Could not have gotten confused even if i tried to, really clear explanation

Amazing explanation!

This is fantastic. I'm a software engineer currently learning about why our cosine similarity functions aren't doing so hot on our large embeddings vector for a large language model. This helps me understand what's happening behind the scenes much better. Thank you!

Really good explanation! Helping me write my first manuscript :)

Great summary, thanks Matthew

Holy fuck is this video good

How to calculate the p value(probability of the distance) in R manually? I don't want to use the function ks.test

Really great - i like the nod to regressions. Our Professor was not very good at explaining that the name Anova is somewhat vague or more a Header-name for different tools. And i got confused when everything was called Anova yet the approaches were somewhat different

Concise and right to the point. I love it. Thanks.

Country X has 30 states with repeated observation measures of X across 15 years for each state. Is Mixed Effects appropriate to model Y from X with states as random effects?

Legend

are you sure it is not possible to do the Hotelling T2 Test in within-desgings? My professor told me to do the test, even though the same group of people did multiple tests on 2 different days.

Hi Matthew, what sources did you use in this video? specifically what sources did you use to distinguish the difference between a ripple and dune?

I am new to this model and I have to say that this video is really helpful! Thanks!

The bext explanation I've found, thank you!