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Lauriane Run

Dorcas Via

Great

Nice

This looks a lot look dplyr with pipes. How do they differ and which do you prefer?

Do you have a tutorial where you use R and python in a dockerized application

It doesn't even have central tendency, your recommendation is flawed bruh

She's a great teacher, her yt channel "a probability space" has some fantastic lectures, very easy to follow

Could we see your config?

Hey, I love book reviews, just a small criticism: it'd be great to have the name of the book in the title or description somewhere along with author :) Just makes it easier to find!

Good book, and it’s one of several on my shelf. However, it was very obviously rushed, with too many samples of areas, with too little practical integration of concepts. Equations are not the same as algorithms, only a small part of it. It is missing much of the other descriptive, let alone instructional aspects. Where are the algorithms described? Where are the conceptual frameworks? Where is the intuition and implications? Where is all the sequencing and pseudocode? Where are the illustrations? Where are the examples? Also, a few more passes would have helped with errors and readability. It was early, primitive and rushed.

😌 'Promo sm'

I studied under Jem. She’s a true gem.

Which book did you refer to for this?

what about all of statistics by Wassermann

Thank you for the video. I have a question: I would like to review some scientific studies, particularly their use of statistics (confidence intervals, the well-known p-values, etc). Could you please recommend a book for this purpose?

2016 though. Much has changed since then. We need a 2024 edition.

Great video, helped me use sql better from terminal, thx!

Thank you very much for the video. I am unable to read the PDF file. Any suggetions ?

*Thanks!* Thanks for making these kind of amazing content.

Can you do the same magic for important research topics and the stuff in the related most cited papers

What a great way of telling about a Mathematics book, its contents and usage. I subscribed immediately and spreading word about you. Really Inspiring. Keep up the good work.

Teaching students to make charts to do formula calculations helps students too. I tell some of them that it it training wheels until they don't need it. Cheerful Calculations 🧮.

Ah yes, probability triples -- that concept shown at the beginning of every stochastic processes book exactly once and then never mentioned again.

مرحبا كيف يمكن ان احصل على نسخه من هذا الكتاب الجيد والمفيد

Would like to see more videos on measure theory. Thanks.

“The first two chapters should be enough to get you into a data science position.” Yeah, only how do I convey this information to the hiring major, whose background is in communications.

Amazing 😊

This was the book we used and it is amazing!

Do you think they're openly negotiated or openly problemd out to a public

statistics is really useful, Mike Lindell is quite good at it actually.

This book completely changed how I thought about cross-sectional data.

I think In my math stats class we used a different book but my teacher had a print out of that diagram of the distributions from this book that my instructor gave us

There are some printing mistakes in Chapter 10. E.g. page 489, Theorem 10.3.1 proof has wrong expression for -2*log(lambda(x)). Some of the proofs in the chapter are not complete, they are sketchy, with just a mention of Slutsky's theorem.

Im a beginner and just learned mathematical statistics from videos Is this book convenient to start with?if not could you recommend please?

a link to have this book ?

Casella and Burger

Personally I really like the various Statistical Learning books by Hastie/Tibsharini - building intuition is probably the most important thing you need in statistics and they were absolutely incredible in doing that (rather than just focusing on dry proofs where you may understand how something is true but not any of the insights behind this). Probably not a good first text as it's more geared towards specifically the applications of statistics but probably the best textbook I've ever read

Really wanna get this, can't find any good sellers online. Appears build/production quality is poor

This is a phenomenal colorscheme! What it its name? Or do you have the list of colors?

I like Jun Shao's book "Mathematical Statistics" (2e), or, at a lower level: "Mathematical Statistics, Old School" by John Marsden

What are the perquisites?

Any one have an undergrad level book recommendation that's good for conditional probability and Bayes and Bayesian inference?

How about an ISBN number, or a solutions manual. That would be helpful.😶

As long as it uses single-letter variable and single-letter greek, no math book is good.

Worst physically printed book ever. Inner pages wrinkled… covers wrinkled… a wreck. Makes me mad ever time I open the book. Boo!

Bro I want a textbook that gives me the understanding of the subject but all applications are done by using matlab or python. What would you recomend?

What would you recommend for at an undergraduate level for someone who's only completed analysis (abbott)? Im self studying math btw

All problems are solved?

I loved this book back in my CS grad school days. I took a few stats courses outside the dept. and one of the courses used this book and I fell in love with stats primarily due to this book. I still have a copy that I go back to once in a while.