Do you have plans to cover books on Operations Research? It's an under-appreciated field of applied mathematics, and the textbook Operations Research by Hillier and Lieberman is the most popular introductory text for the topic. Thanks for reading!
Things I'd like to see you cover ... - History of randomness in programming. - History of Math Filters. - The history of the transition between using tables for logs and trig results to calculators. - History of "How Math is Taught over the years, in terms of the refinement of math books (pictures and explanations)."
Robert Gallager is a legend in the field of error correction coding theory. In his excellent 1970’s textbook entitled Information Theory and Reliable Communications, he describes his novel scheme for attaining extremely efficient error correction (in the sense of approaching the Shannon limit arbitrarily close). Now called low density parity check (LDPC) codes his concept was only theoretical curiosity due to a large computational overhead at the time.
Wow I literally just got this book out from my university library the other day and was looking to see if you had a video on it last week. Now you do! Mathematical statistics, probability theory and stochastic processes is my favourite flavour of mathematics.
Sheldon Ross’ books always delivers on content but can seem a tad terse for the beginner. The subject of Stochastic Processes is no walk in the park even for the mathematically mature. As an alternative I suggest the pedagogical masterpiece written by the late Athanasios Papoulis titled Probability, Random Variables and Stochastic Processes.
I have this book as well, it covers the same topics as Ross's book and also has some other interesting topics pertaining to electrical engineering like entropy, ergodicity, spectrum estimation etc. I found the book you recommended much better than Ross's book. However, I do believe that its intro probability and statistics section was not that great -> as in I do think that going through Ross's First course in probability then Casella's Inference would be a good build up to Part 2 of Papoulis's book (u can skip part 1 that way)
I totally agree with this note about A.Papoulis, he was a great tech-math and pioneer master professor in NY Polytechnic. By the way, I own the "Probability Models " by Sheldon Ross, a great book in a cheap Dover edition. Classical Books like: Karlin-McGregor, Erhan Cinlar, Battachariya, E.Parzen, Box-Jenkins and more theoretical M.Loeve,(and John Doob of course) and W.Feller are of great value too.
I'm not sure about this particular book, but generally if I can have some of the back answers provide enough guidance, it gets me through the missing answers. This isn't always the case, since I've found curve balls where some of the even numbered, non-answered questions are from left field. I think they put those in to give teachers options for their classes.
I didn't like it, but Probability Models by Ross was a pretty much a foundation stone for my actuarial career. If you're going that route, I recommend "Loss Models" by Klugman, Panjer and Willmot as your next book.
Probability and statistics, in the most basic terms, are becoming so important in everyday life nowadays that there are advocates in the Educational sphere wondering if a proper introduction to Mathematics after the basics towards entering college should be less Calculus based, and more Statistics and Probability based, as a foundation. So, it someone ever stops taking more Math or going to a different learning path, that person will be better served with at least some notitions in those topics instead on Calculus topics, for the rest of his life. It is an ongoing debate, I was told.
They actually tried this in California, where students would take introductory statistics instead of algebra 2. I personally do think that statistics is more important than ever, but it isn't more important that calculus for certain people. Let me tell you why: If someone is in a STEM track, then it makes more sense to take calculus in high school, preferably up to vector calculus before going into college. Many of these STEM degrees already require statistics -> for example many math majors take probability, many bio majors take biostats, engineers might take statistical DSP or statistical thermodynamics etc. In many schools, comp sci majors take a statistical inference course to. In that regard, I do think that STEM focused students in high school can neglect taking statistics as they will need to in undergrad anyway. Now to my point about NON STEM majors. If someone is interested in History for example, it will be more useful for them to take statistics/economics than to take calculus. For example if we were to redo the HS syllabus to do 3 years of calculus, maybe the History students would take 1 year of stats, 1 year of micro, 1 year of macro (just an example). Non stem majors taking statistics [and I would like to add economics] would be very beneficial for society in general as the HS diplomas would leave school with a better understanding of the world, a better understanding than if they bullshit their way out of AP Calc AB.
I was thinking about studying stochastic processes over the summer, I was wondering how useful is this type of math for actuarial science as I am in my 2nd year for the degree
Can I ask what you focused on in college? Not formal names for concentrations but in your own eyes, what were you more or less focusing on in mathematics during your undergraduate and graduate studies? Were you interested in and tailoring your degree towards probability theory, mathematical statistics, math modeling, etc?
An updated version of this book is used in UCLA's undergraduate stochastic processes class that I took, professor was bad, but the book was good
I also took a graduate course on stochastic processes as an elective. It was an interesting but challenging class.
Do you have plans to cover books on Operations Research? It's an under-appreciated field of applied mathematics, and the textbook Operations Research by Hillier and Lieberman is the most popular introductory text for the topic. Thanks for reading!
Things I'd like to see you cover ...
- History of randomness in programming.
- History of Math Filters.
- The history of the transition between using tables for logs and trig results to calculators.
- History of "How Math is Taught over the years, in terms of the refinement of math books (pictures and explanations)."
Robert Gallager's MIT OCW class/lectures on discrete stochastic processes was lovely, for anyone interested.
Robert Gallager is a legend in the field of error correction coding theory. In his excellent 1970’s textbook entitled Information Theory and Reliable Communications, he describes his novel scheme for attaining extremely efficient error correction (in the sense of approaching the Shannon limit arbitrarily close). Now called low density parity check (LDPC) codes his concept was only theoretical curiosity due to a large computational overhead at the time.
Wow I literally just got this book out from my university library the other day and was looking to see if you had a video on it last week. Now you do! Mathematical statistics, probability theory and stochastic processes is my favourite flavour of mathematics.
Sheldon Ross’ books always delivers on content but can seem a tad terse for the beginner. The subject of Stochastic Processes is no walk in the park even for the mathematically mature. As an alternative I suggest the pedagogical masterpiece written by the late Athanasios Papoulis titled Probability, Random Variables and Stochastic Processes.
I have this book as well, it covers the same topics as Ross's book and also has some other interesting topics pertaining to electrical engineering like entropy, ergodicity, spectrum estimation etc. I found the book you recommended much better than Ross's book. However, I do believe that its intro probability and statistics section was not that great -> as in I do think that going through Ross's First course in probability then Casella's Inference would be a good build up to Part 2 of Papoulis's book (u can skip part 1 that way)
I totally agree with this note about A.Papoulis, he was a great tech-math and pioneer master professor in NY Polytechnic. By the way, I own the "Probability Models " by Sheldon Ross, a great book in a cheap Dover edition. Classical Books like: Karlin-McGregor, Erhan Cinlar, Battachariya, E.Parzen, Box-Jenkins and more theoretical M.Loeve,(and John Doob of course) and W.Feller are of great value too.
Stochastic processes is challenging.
I'm not sure about this particular book, but generally if I can have some of the back answers provide enough guidance, it gets me through the missing answers. This isn't always the case, since I've found curve balls where some of the even numbered, non-answered questions are from left field. I think they put those in to give teachers options for their classes.
I've got a book from Ross on Probability Models sitting on my desk right now as I clicked on this video from you! His books are dense and fast-paced.
I didn't like it, but Probability Models by Ross was a pretty much a foundation stone for my actuarial career. If you're going that route, I recommend "Loss Models" by Klugman, Panjer and Willmot as your next book.
@@M3GAprincess I also used his book to prepare for when I took exam P
@@BobbyMack Good for you. I used mostly Actex to drill the problems for P and FM, both those are sort of speed tests more than comprehension (IMO).
I don't understand why they don't include all the answers
Probability and statistics, in the most basic terms, are becoming so important in everyday life nowadays that there are advocates in the Educational sphere wondering if a proper introduction to Mathematics after the basics towards entering college should be less Calculus based, and more Statistics and Probability based, as a foundation. So, it someone ever stops taking more Math or going to a different learning path, that person will be better served with at least some notitions in those topics instead on Calculus topics, for the rest of his life. It is an ongoing debate, I was told.
They actually tried this in California, where students would take introductory statistics instead of algebra 2. I personally do think that statistics is more important than ever, but it isn't more important that calculus for certain people. Let me tell you why: If someone is in a STEM track, then it makes more sense to take calculus in high school, preferably up to vector calculus before going into college. Many of these STEM degrees already require statistics -> for example many math majors take probability, many bio majors take biostats, engineers might take statistical DSP or statistical thermodynamics etc. In many schools, comp sci majors take a statistical inference course to. In that regard, I do think that STEM focused students in high school can neglect taking statistics as they will need to in undergrad anyway. Now to my point about NON STEM majors. If someone is interested in History for example, it will be more useful for them to take statistics/economics than to take calculus. For example if we were to redo the HS syllabus to do 3 years of calculus, maybe the History students would take 1 year of stats, 1 year of micro, 1 year of macro (just an example). Non stem majors taking statistics [and I would like to add economics] would be very beneficial for society in general as the HS diplomas would leave school with a better understanding of the world, a better understanding than if they bullshit their way out of AP Calc AB.
The Ethernal War between Pure and Applied Maths.....
I never understood the reason of a book of problems without answers to those problems 😅
There is also.one book by OLIVER C IBE on stochastic and probability models...its a beginner book...
I was thinking about studying stochastic processes over the summer, I was wondering how useful is this type of math for actuarial science as I am in my 2nd year for the degree
most of short term models use this. check out SOA exam ASTAM
Your book 📕 looks super neat. I marked all my books 📚 with pen 🖊️ I think 🤔 I have to stop doing that.
I was literally going to ask you about books on this topic!
Do you have books on the calculus of variations?
Hey, what would be a good book/website for someone who wants to work on their math vocabulary to understand what the professors are talking about ?
Can I ask what you focused on in college? Not formal names for concentrations but in your own eyes, what were you more or less focusing on in mathematics during your undergraduate and graduate studies? Were you interested in and tailoring your degree towards probability theory, mathematical statistics, math modeling, etc?
I'm taking a stochastic processes course that uses this same book next semester by the way!
I hope you get a camera (possibly via sponsorship) for clearer pictures
Can you make a video on Dynamical Systems in general, there's so much to it that understanding its purpose is confusing
Love the content,
Cheers
It's a good book for applications but there's no getting your way around stochastic processes if you didn't previously study measure theory.
does anyone have any tips about books on kuhn tucker?
Looking good book
You're like the Sam Harris of mathematics.
his best friend goes to my school.
We need a smell rating on this one, you sniffed it but didn't give us the verdict
I just finished it , I think I will fail. It’s so disgusting and i don’t know why it’s important in our field ( actuary)
Actuaries barely use probability theory. It's all about selling insurance cheaper than the other insurers.
@@jacoboribilik3253 I still have a year and a half to graduate and yes I failed stochastic process. It’s only course I failed until now
my boyfriend kissed another girl twice in a row. enter Rod Stewart. she had nice hair that he helped her with. i miss math and 5,000 books