What a surprise!! I took that class with Prof Anthony Hayter, using that book, at Georgia Tech. I still have it. Good memories. Hayter was a very good professor. I enjoyed his class.
i know it's not about the video theme but, just wanna tell you're helping me a lot with motivation and a way to think and learn math, i'm from Brazil and doing computer science so i was scared with all the math around it and started to learn math from scratch again, thank you!
I will try to find that book. Thanks. I enjoy prob and stats. When I first learned probability we first had to learn basic combinatorics (binomial coefficient, etc.) ad nauseam for coins, dice, poker which really helped to later tackle probability questions. I bet that is covered in 1.7 of this book "counting techniques".
Abel Prize 2024, "I know a guy who won't learn much by reading this book. The 2024 Abel Prize is awarded to Michel Talagrand, former CNRS research director at the Institute of Mathematics of Jussieu - Paris, France, for his revolutionary contributions to probability theory and functional analysis."
Hi, thanks for this recommendation. I have been looking for a Probability and Statistics book to learn from that emphasizes applications but does not skip over probability foundations (sets, events, sample spaces, probability laws, Bayes, etc). I expect a book for scientists and engineers is the best category to look into. I was thinking between 1) Walpole 9th Ed, 2) Navidi 6th Ed, or 3) Miller & Freund (updated by Johnson) 9th Ed. I like that Walpole has a final chapter on Bayesian Statistics (which I'd like to learn about) and Miller-Freund has a final chapter on Reliability. Miller-Freund seems to be kind of weak in its probability though. Navidi seems solid, but it does not have any stand-out topics and I do not have enough Prob/Stats background to say whether I should go with it. Maybe Hayter is a good option. I know you haven't read every math book in existence, but If you have any input that would be awesome. I get FOMO when choosing books to self study from and I want to make sure I get a good foundation and I also want to have a good framework for applying Prob/Stats.
SAS is used for statistical computations in the pharmaceutical industry these days; the FDA requires SAS. This is obviously an important topic in applied mathematics.
I enjoyed both these subjects more than I thought I would before I took them. We didn't use that book, but it's less apt to throw insurmountable obstacles at the reader than calculus or real analysis would. I would say there's a less than 20% probability that anyone reading this book would get stuck and become unable to move forward when compared to any topology or real analysis book, both which give about a 100% probability even if aided by a teacher. For problem 3.1.5 at time 8:57, since two d6 would be 6^6 per each probability, would 8d6 = 6^8? That table would be huge. But for 1 even number, it would be 1/2 of that table or 1/(6^8)*1/2.
Could you review "Mathematical Logic" by Jospeh R. Shoenfield ? I currently reading your recommended book "Principles of Logic" by Alex C. Michalos and it's great. I am thinking of reading "Mathematical Logic" next.
I'd be really curious to know what your thoughts are on Probability Theory by Jaynes. So many people refer to it as a paradigm shift and the only probability book you'll ever need. I know he has some different takes so curious what you think
That’s a great one. My university uses it for a 4th year course. The exercises are tough. Apparently, the University of Toronto uses it for their 2nd year (albeit upper division) intro stat course
Quick Question, is Probability and Statistics, 1 subject? I am guessing it means this book is a "Probability textbook' that uses statistics to showcase the results. Same as "Business Growth and Statistics" meaning it uses statistics to project business growth?
Adminitratively, probability and statistics are usually separate courses (for math majors at least). They are related but are fundamentally different subjects: in probability theory, a data generating mechanism (e.g. tossing a fair coin) is assumed and the goal is to *deduce* the characteristics of its output without actually witnessing any actual data; in statistics that process is reversed, namely, we only have observations and the goal is to *infer* what the data generation mechanism is. Traditional statistical science makes heavy use of probability theory though, so usually a course on probability is a prerequisite for a course on statistics.
That was kind of my reaction to statistics when I was a math major: I avoided it and never took a class in it, partly because I didn't think of it as "real math" but as number-crunching and data manipulation and boring stuff like that. But later I got around to studying it on my own and found it a lot more mathematically interesting than I expected.
@@Steve_Stowersperhaps it was due to the way intro stats courses are taught most of the time. Pretty uninspired imo. Typically students were just thrown a bunch of formula with little motivation or explanation. E.g. very few undergraduates end up understanding what p-value is and why is it defined so (let alone the controversy surrounding it) out of an intro stat course
How is someone a math major but hates statistics 😭 that person probably shouldn’t be a math major some math subjects suck but you are a math major you should want to do math all types of math
Let's see the chapters on an intro to combinatorics, or the joint distribution of random variables, or I wanted to see what they had for an intro to multiple linear or nonlinear regression. :) But it was cool to see the formula for negative binomial distribution. Takes me back.
What a surprise!! I took that class with Prof Anthony Hayter, using that book, at Georgia Tech. I still have it. Good memories. Hayter was a very good professor. I enjoyed his class.
i know it's not about the video theme but, just wanna tell you're helping me a lot with motivation and a way to think and learn math, i'm from Brazil and doing computer science so i was scared with all the math around it and started to learn math from scratch again, thank you!
Ultimamente ando vendo muitos brasileiros aqui tbm. Muito bom!
@@victornecromancer o cara é fera
On monday i passed probability-theory and statistics in the university^^ this books looks interesting to have some more problems to solve^^
I used Applied Stats & Prob by Montgomery & Runger. I liked it a lot. The book also has more than 1000 exercises!!!
I will try to find that book. Thanks. I enjoy prob and stats. When I first learned probability we first had to learn basic combinatorics (binomial coefficient, etc.) ad nauseam for coins, dice, poker which really helped to later tackle probability questions. I bet that is covered in 1.7 of this book "counting techniques".
What a historical trip with that disk drive as well ! Boom💥
Abel Prize 2024, "I know a guy who won't learn much by reading this book. The 2024 Abel Prize is awarded to Michel Talagrand, former CNRS research director at the Institute of Mathematics of Jussieu - Paris, France, for his revolutionary contributions to probability theory and functional analysis."
Hi, thanks for this recommendation.
I have been looking for a Probability and Statistics book to learn from that emphasizes applications but does not skip over probability foundations (sets, events, sample spaces, probability laws, Bayes, etc). I expect a book for scientists and engineers is the best category to look into. I was thinking between 1) Walpole 9th Ed, 2) Navidi 6th Ed, or 3) Miller & Freund (updated by Johnson) 9th Ed. I like that Walpole has a final chapter on Bayesian Statistics (which I'd like to learn about) and Miller-Freund has a final chapter on Reliability. Miller-Freund seems to be kind of weak in its probability though. Navidi seems solid, but it does not have any stand-out topics and I do not have enough Prob/Stats background to say whether I should go with it. Maybe Hayter is a good option.
I know you haven't read every math book in existence, but If you have any input that would be awesome. I get FOMO when choosing books to self study from and I want to make sure I get a good foundation and I also want to have a good framework for applying Prob/Stats.
SAS is used for statistical computations in the pharmaceutical industry these days; the FDA requires SAS. This is obviously an important topic in applied mathematics.
I enjoyed both these subjects more than I thought I would before I took them. We didn't use that book, but it's less apt to throw insurmountable obstacles at the reader than calculus or real analysis would. I would say there's a less than 20% probability that anyone reading this book would get stuck and become unable to move forward when compared to any topology or real analysis book, both which give about a 100% probability even if aided by a teacher.
For problem 3.1.5 at time 8:57, since two d6 would be 6^6 per each probability, would 8d6 = 6^8? That table would be huge. But for 1 even number, it would be 1/2 of that table or 1/(6^8)*1/2.
Could you review "Mathematical Logic" by Jospeh R. Shoenfield ?
I currently reading your recommended book "Principles of Logic" by Alex C. Michalos and it's great.
I am thinking of reading "Mathematical Logic" next.
I'd be really curious to know what your thoughts are on Probability Theory by Jaynes. So many people refer to it as a paradigm shift and the only probability book you'll ever need. I know he has some different takes so curious what you think
Have you seen Statistical Inference by Casella and Berger? It's a masters level text.
That’s a great one. My university uses it for a 4th year course. The exercises are tough. Apparently, the University of Toronto uses it for their 2nd year (albeit upper division) intro stat course
@@mingmiao364 I believe it. The US math requirements seem low in comparison to other countries. I won't see it in a formal class till a masters.
Boy, this is for Im searching, Probability and Statistics book, even I search on your channel about it.
The impacts of probability are even more profound to be applied in real world engineering problems.
You have a lot of nice math books. How much money approximately did you spend in them?
Quick Question, is Probability and Statistics, 1 subject? I am guessing it means this book is a "Probability textbook' that uses statistics to showcase the results. Same as "Business Growth and Statistics" meaning it uses statistics to project business growth?
Adminitratively, probability and statistics are usually separate courses (for math majors at least). They are related but are fundamentally different subjects: in probability theory, a data generating mechanism (e.g. tossing a fair coin) is assumed and the goal is to *deduce* the characteristics of its output without actually witnessing any actual data; in statistics that process is reversed, namely, we only have observations and the goal is to *infer* what the data generation mechanism is. Traditional statistical science makes heavy use of probability theory though, so usually a course on probability is a prerequisite for a course on statistics.
Man this subject is hard, i believe that sometimes it is even harder than calculus
Statistics isn't Just prob disyribution,there're some topics that are really hard like statistics theory.
Just when I started learning these two subects, the math sorcerer comes to save me, maybe that's why he is the sorcerer.
What's your opinion of brilliant and it's maths courses
I was looking for a good statistics book, great!
Ahh the t dist. Crucial for making good beer. 🍺 Brilliant!
I have a copy of the Triolla book, is it goot to start or better get another?
Whenever I bring up statistics to a math major, the only reaction I get is eww 😂 Hopefully you will be the one who change their mind
That was kind of my reaction to statistics when I was a math major: I avoided it and never took a class in it, partly because I didn't think of it as "real math" but as number-crunching and data manipulation and boring stuff like that. But later I got around to studying it on my own and found it a lot more mathematically interesting than I expected.
@@Steve_Stowersperhaps it was due to the way intro stats courses are taught most of the time. Pretty uninspired imo. Typically students were just thrown a bunch of formula with little motivation or explanation. E.g. very few undergraduates end up understanding what p-value is and why is it defined so (let alone the controversy surrounding it) out of an intro stat course
How is someone a math major but hates statistics 😭 that person probably shouldn’t be a math major some math subjects suck but you are a math major you should want to do math all types of math
@@acrane3496good point
@@acrane3496 I never thought about it like that.
not a floppy disk a 'stiffy' disk
Any idea of text books of applied statistics including copulas pour favor ?
Let's see the chapters on an intro to combinatorics, or the joint distribution of random variables, or I wanted to see what they had for an intro to multiple linear or nonlinear regression. :) But it was cool to see the formula for negative binomial distribution. Takes me back.
Did my book recommendation get deleted?
Aw man I barely passed with a C and it was my first semester after dropping out, as a CS major I think I should try to learn this again...
I want pdf of this book can anyone share the link
I used the Sheldon Ross book with the same title
Stats: 2+2 is 4, and whaaa, I don't like it. Make it equal 38.
Hard subject for me
First!