No one would believe how much I waited for this playlist. I will start following the series by the end of this month after my optimization for data science course. Deepest Love and Respect from Pakistan ♥.
I also recently bought your book (2 chapters in) and i’ll be taking stat inference 2 this semester (we’ll cover the second half of Casella and Berger). Your book is a great supplement and i’m looking forward to watching the videos too! Thank you for uploading!
What a treat this new series is. I just bought your book yesterday and I am hooked to it. Gonna follow your lectures in parallel. Although I am not new to statistics, but I am looking forward to seeing it from your lens 😊
Thank you for the series! Really great. In the videos you reference the notes and homework exercises. Can you share those with your RUclips audience please?
I'm enjoying this so far. I just started my master's. Fall was my first 3 credit course (Applied Linear Models). My wife passed away in fall of 2023 so I decided to do something to keep busy and keep my mind active. I have no real reason to do this other than that, since I'm in the twilight of my career. However, I could retire and do some consulting with a Master's .
Thank you for sharing. I'm very sorry for your loss but I think your goal is wonderful and I think you'll really enjoy some of the cool courses you'll get to take. All the best!
I’m considering going back to school for statistics. Thank you for going through the trouble of making and providing these videos, it gives an interested layperson a chance to see what the topic is like.
I just went back in fall for Master's of Applied Statistics. I'm 59 years old. It's definitely a challenge as I have had to relearn a lot of things I had forgotten from 37 years ago during my undergrad. I haven't seen an integral sign or matrix in almost 4 decades, so it's been a lot of work trying to relearn the old and learn the new. I wish I had done it years ago.
I love this series more than I can possibly express. I've painfully completed a time-series modeling and a Bayesian inference class without having this foundational material, and am now rushing to complete it before my Statistical Learning and Deep Learning classes start next year. I bought your book so I could follow along and do the exercises. Would love to know which exercises you assign for each lecture.
You have no idea how happy it makes me to hear this. Thank you! As for the exercises, I don't know off the top of my head but I'll try to get back to this comment within the next few days after looking for the assignments. Thanks again!
Thanks a lot, these are really excellent videos. As a PhD student whose research is related to machine learning, I should say I always want to review my statistic knowledge and learn some advanced things, and this set of videos is really what I want. By the way, hope that someday you can teach a course about stochastic calculus, I am really interested in this part, since I always want to really understand the diffusion models.
The topic names are in the description boxes. I don't know how to put them into the titles without making the titles really messy because each video has multiple topics!
Professor , I am following the previous playlist that you have uploaded. Will there be any significant difference in this new series since I am halfway done with the old one ?
There will be some differences but no, not significant. The old playlist is kind of messy though. It had some missing videos for which I put in close substitutions so it might seem a little weird and fragmented at times. While the new playlist will be much better, I don't think it is worth it to switch if you are halfway in. Thanks.
I remember this material from my days at UF in the 70's. What strikes me now is the same as what struck me then, is that the terminology, variable names, and shorthand of nearly everything is actually the major impediment to learning the material. Note when hand writing for example, that the only person who knows whether x is x or X is the instructor! The variable naming scheme in statistics and probability seems almost purposely attrocious. And once a student becomes confused about even one symbol, they are lost and there is not much chance that they will be able to catch up. I remember thinking to myself that the instructor had their way of doing things memorized and that the way they taught was to treat everything like it is so obvious that deriving the material as you go is trivial. It implies that once you know everything about Statistics you now are finally equipped to understant the first lecture. It's like taking something of difficulty 5 and explaining it in such a way that it now becomes difficulty 10.
@@AProbabilitySpace I wish the course wouldn't say, "this is a chi-square distribution". It should say, "situations like this revealed that there is a distribution like this occurring that we eventually came to call the chi-square distribution"
@@CaptainAhab-im3kd Sure, it was originally defined for something observed, but now it IS the chi-squared distribution so there's nothing wrong with bringing it out and saying "this is a chi-squared distribution"! 🙂
@@AProbabilitySpace I guess you are assuming that no one cares what situation it was where it was observed. That is what I find hard to accept, because it makes it look like the chi-square is just something mathematicians made up simply because it was doable as a theoretical analysis and who cares if it occures in nature or not. I guess all that gets covered in the basic course, which was a course I never got the opportunity to take, unlike most of the students in mathematical statistics. A basic course was not required at UF at the time, but instructors assumed it was a given that everyone in the class had already taken it, a major bad assumption!! I majored in chemical engineering and had opportunity for only about three electives. This was a difficult course for me as a sophomore. I struggled just to get through it mainly because I was not relating to the context of what we were trying to learn. Most students in the class were attending to try to get Master's degrees it seemed.
Waw what an exciting channel I have ever found, what are the prerequisities for this course? Is it like advanced statistical theory (probabilty theory) course from CMU? Probability and statistics will enough for this one? :)
Wow this looks great. What is the relationship between these lectures and the Coursera 'Data Science Foundations' specialization? I'm just thinking about a source of homework problems etc, for those who are not studying at your university.
Thank you @browncow7113. Those courses are very different. The Coursera ones are much more data oriented while Mathematical Statistics is quite theoretical. However, you've just convinced me that I need to be posting homework problems here so I'm going to start doing that this week!
@@conchobar0928 Sorry, not yet. I do have some exercises and solutions with some of the videos. Every time I go over HW problems, I make sure to explain the setups completely so you can also get some from the videos!
hi, i did math stats, anova and regression end of last year, this year i did stochastic and im currently doing time series. I want to deepen my stats knowlege any sugestions on which courses i should do next to know more stats in general?
No one would believe how much I waited for this playlist. I will start following the series by the end of this month after my optimization for data science course. Deepest Love and Respect from Pakistan ♥.
I also recently bought your book (2 chapters in) and i’ll be taking stat inference 2 this semester (we’ll cover the second half of Casella and Berger). Your book is a great supplement and i’m looking forward to watching the videos too! Thank you for uploading!
Thank you!
What an absolute 10. I think I'm in love.
What a treat this new series is. I just bought your book yesterday and I am hooked to it. Gonna follow your lectures in parallel. Although I am not new to statistics, but I am looking forward to seeing it from your lens 😊
Thank you!
iitk? A kanpurite?
Thank you for the series! Really great.
In the videos you reference the notes and homework exercises. Can you share those with your RUclips audience please?
I'm enjoying this so far. I just started my master's. Fall was my first 3 credit course (Applied Linear Models). My wife passed away in fall of 2023 so I decided to do something to keep busy and keep my mind active. I have no real reason to do this other than that, since I'm in the twilight of my career. However, I could retire and do some consulting with a Master's .
Thank you for sharing. I'm very sorry for your loss but I think your goal is wonderful and I think you'll really enjoy some of the cool courses you'll get to take. All the best!
I'm so excited for this playlist! I'll be buying the book promptly and can't wait to follow along
Aw, thank you so much!
This mathematical statistics series is so valuable. Please upload the entire series. I am ordering your textbook to follow along this whole lecture.
Thank you!
I’m considering going back to school for statistics. Thank you for going through the trouble of making and providing these videos, it gives an interested layperson a chance to see what the topic is like.
Do it! 😀
@@AProbabilitySpace thanks! Do you have any suggestions about the career prospects in the field right now? I would be a career changer.
I just went back in fall for Master's of Applied Statistics. I'm 59 years old. It's definitely a challenge as I have had to relearn a lot of things I had forgotten from 37 years ago during my undergrad. I haven't seen an integral sign or matrix in almost 4 decades, so it's been a lot of work trying to relearn the old and learn the new. I wish I had done it years ago.
@@jimturner4937hey Jim, same here! Took math stats this fall, was tough but I passed. Notorious professor.
I saw the first two courses of the specialization last month. It was amazing. The basics were clear. I'm gonna check this course for sure.
I love this series more than I can possibly express. I've painfully completed a time-series modeling and a Bayesian inference class without having this foundational material, and am now rushing to complete it before my Statistical Learning and Deep Learning classes start next year. I bought your book so I could follow along and do the exercises. Would love to know which exercises you assign for each lecture.
You have no idea how happy it makes me to hear this. Thank you! As for the exercises, I don't know off the top of my head but I'll try to get back to this comment within the next few days after looking for the assignments. Thanks again!
Great explanation.
Thank you!
Wow I enjoyed this! I didn’t know none of this until now. Thank you 😊
Thank you for the kind words! :)
This is awesome! Great explanations and you make the topic fun! This is really useful for leaning AI.
Great to hear! Thanks!
Can we get the material? Like the distributions handout and the couse notes?
Thanks a lot, these are really excellent videos. As a PhD student whose research is related to machine learning, I should say I always want to review my statistic knowledge and learn some advanced things, and this set of videos is really what I want. By the way, hope that someday you can teach a course about stochastic calculus, I am really interested in this part, since I always want to really understand the diffusion models.
Also, I am waiting for your update of your measure theoretic probability course♥
35:55 must be the greatest academic moment I've ever witnessed
Ma'am can you add topic names along with lecture titles, it would be helpful for readability.
The topic names are in the description boxes. I don't know how to put them into the titles without making the titles really messy because each video has multiple topics!
Doing FE610 Stochastic at Stevens in the Fall part of Msc Fin Eng, prepping up, this is great
Who is this diva and I need her as my professor
this is pretty nice, is there a course website for syllabus?
Professor , I am following the previous playlist that you have uploaded. Will there be any significant difference in this new series since I am halfway done with the old one ?
There will be some differences but no, not significant. The old playlist is kind of messy though. It had some missing videos for which I put in close substitutions so it might seem a little weird and fragmented at times. While the new playlist will be much better, I don't think it is worth it to switch if you are halfway in. Thanks.
where can i buy the e-book?, its seems like a physical book at the amazon link.
I remember this material from my days at UF in the 70's. What strikes me now is the same as what struck me then, is that the terminology, variable names, and shorthand of nearly everything is actually the major impediment to learning the material. Note when hand writing for example, that the only person who knows whether x is x or X is the instructor! The variable naming scheme in statistics and probability seems almost purposely attrocious. And once a student becomes confused about even one symbol, they are lost and there is not much chance that they will be able to catch up. I remember thinking to myself that the instructor had their way of doing things memorized and that the way they taught was to treat everything like it is so obvious that deriving the material as you go is trivial. It implies that once you know everything about Statistics you now are finally equipped to understant the first lecture. It's like taking something of difficulty 5 and explaining it in such a way that it now becomes difficulty 10.
I'm sorry that you had such a bad experience! 🙁
@@AProbabilitySpace I wish the course wouldn't say, "this is a chi-square distribution". It should say, "situations like this revealed that there is a distribution like this occurring that we eventually came to call the chi-square distribution"
@@CaptainAhab-im3kd Sure, it was originally defined for something observed, but now it IS the chi-squared distribution so there's nothing wrong with bringing it out and saying "this is a chi-squared distribution"! 🙂
@@AProbabilitySpace I guess you are assuming that no one cares what situation it was where it was observed. That is what I find hard to accept, because it makes it look like the chi-square is just something mathematicians made up simply because it was doable as a theoretical analysis and who cares if it occures in nature or not. I guess all that gets covered in the basic course, which was a course I never got the opportunity to take, unlike most of the students in mathematical statistics. A basic course was not required at UF at the time, but instructors assumed it was a given that everyone in the class had already taken it, a major bad assumption!! I majored in chemical engineering and had opportunity for only about three electives. This was a difficult course for me as a sophomore. I struggled just to get through it mainly because I was not relating to the context of what we were trying to learn. Most students in the class were attending to try to get Master's degrees it seemed.
I am currentlt taking a prob and stats class for engineers. I have no prob and stats background will I have trouble keeping up with this course?
Waw what an exciting channel I have ever found, what are the prerequisities for this course? Is it like advanced statistical theory (probabilty theory) course from CMU? Probability and statistics will enough for this one? :)
Any basic course in probability should be enough. :)
Wow this looks great. What is the relationship between these lectures and the Coursera 'Data Science Foundations' specialization? I'm just thinking about a source of homework problems etc, for those who are not studying at your university.
Thank you @browncow7113. Those courses are very different. The Coursera ones are much more data oriented while Mathematical Statistics is quite theoretical. However, you've just convinced me that I need to be posting homework problems here so I'm going to start doing that this week!
@@AProbabilitySpaceYay, homework!
@@browncow7113 Haha!
@@AProbabilitySpace I can't find the homework problems, have they been posted on your channel? 😊
@@conchobar0928 Sorry, not yet. I do have some exercises and solutions with some of the videos. Every time I go over HW problems, I make sure to explain the setups completely so you can also get some from the videos!
You present the course very rigorously, thank you so much. Are the notes available for RUclips users?
Unfortunately, I can no longer provide them due to a recent publishing contract I have. Sorry... 😥
Very clear presentation! May I ask which app in IPAD do you use for your presentation?
Thank you. I use Notability. :)
Maam can i follow this playlist to learn stats and probability for my CS courses like machine learning etc
thank youuu
Great lecture. How to get the book?
Thank you so much. I just added the book link in the description box.
@@AProbabilitySpace Thank you, Professor. I found it on Amazon.
@@sanohyusuf9534 Thank you for your support!
a background from half-life-alyx cool!
Good catch!
Hello, what software is the professor using to display the formulas?
Does this course qualify me for the markov processes ?
Yes!
omg i wish i could be her student
Hello professor. what are the prerequisites for taking this course?
hi, i did math stats, anova and regression end of last year, this year i did stochastic and im currently doing time series. I want to deepen my stats knowlege any sugestions on which courses i should do next to know more stats in general?
Sorry about the delay. Have you taken any Bayesian stats courses?
@@AProbabilitySpace no, only the courses mentioned above and probability theory
Hi, how can I access the Canvas website with materials?
Is it only accessible to CU students?
@@qtyLimetest Unfortunately, yes. I will try to add some links to materials from youtube later this week!
@@AProbabilitySpace thanks for the comment. I really like this lecture :)
i.m looking forward to seeing a fish of length zero.
They are all around you. Don't you see them? 😁
@@AProbabilitySpace 🤣