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Let's Learn, Nemo!
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Добавлен 26 дек 2018
Hello there! This channel is meant to provide a thorough treatment of most mathematical subjects that are encountered in universities. The goal's to update playlists as they should be updated when new topics come about in applications to the real world and update videos in case the audience does not like them; the goal is to help you gain a better understanding and to increase your strength and interested in mathematics and statistics!
For those who are new to mathematics in general, or want to start somewhere on this channel, Pre-Calculus (Part A) is the best place to start. I include topics that are appropriate to the difficulty in those playlists, even though they may not be (currently) taught in colleges and universities. For example, I introduce tetrations and Lambert W in Pre-Calculus, and Gamma and Riemann Zeta functions in Integral Calculus (to name a few). If you enjoy, please subscribe, and feel free to leave comments on videos if you have questions; I will respond! Enjoy!
For those who are new to mathematics in general, or want to start somewhere on this channel, Pre-Calculus (Part A) is the best place to start. I include topics that are appropriate to the difficulty in those playlists, even though they may not be (currently) taught in colleges and universities. For example, I introduce tetrations and Lambert W in Pre-Calculus, and Gamma and Riemann Zeta functions in Integral Calculus (to name a few). If you enjoy, please subscribe, and feel free to leave comments on videos if you have questions; I will respond! Enjoy!
(MC12) Multiple-Integral Approximations
This session extends the concepts of left, right, and midpoint methods from single-variable calculus to multiple variables, introducing cardinal, intercardinal, and midpoint partitions for more complex integral evaluations. We begin by generalizing these approximation methods to tackle multi-dimensional integrals, providing clear examples to illustrate each approach. The video then shifts focus to an exciting application of probability in calculus-using Monte Carlo methods to approximate areas and integrals. We take a deep dive into how Monte Carlo simulations can be utilized to estimate values such as π, serving as a practical guide to understanding this stochastic technique.
Further, we ...
Further, we ...
Просмотров: 952
Видео
(IS35) Time Series Fundamentals
Просмотров 1,2 тыс.День назад
In this video, we begin by discussing the fundamental differences between regression and time series models, focusing on how time series models account for time-dependent changes and autocorrelations within data sets. Moving forward, we explore two pivotal time series forecasting methods: the Simple Moving Average (SMA) and Exponential Moving Average (EMA). We'll delve into how each model is de...
(LA01) What is a Vector?
Просмотров 1,1 тыс.День назад
This video lays the foundation by defining what vectors are and explaining their critical components: magnitude and direction. We delve into how vectors are represented and interpreted with respect to planar axes, providing a robust understanding of these fundamental mathematical tools. We then move into key operations involving vectors: scalar multiplication, vector addition, and dot products....
(PS10) Probability Mass Functions
Просмотров 81114 дней назад
This video builds on a basic introduction to probability by focusing on the different types of random variables: categorical, discrete, and continuous, and outlines the key properties of their probability mass functions (PMFs) and probability density functions (PDFs). We start with an in-depth look at PMFs, providing clear examples of basic calculations. We then introduce the concepts of expect...
(SC30) Integration of Polar and Parametric Curves
Просмотров 1,1 тыс.21 день назад
We start by deriving the formula for the area enclosed by a region in polar coordinates. Through a practical example, we illustrate how this formula is applied to calculate specific areas, enhancing your understanding of polar integration. Next, we transition to the arc length of polar curves, providing a derivation followed by a detailed example to solidify your grasp of these concepts. The vi...
(SC29) Integral Applications to Economics
Просмотров 67428 дней назад
We begin with an overview of the laws of supply and demand and discuss the significance of the market equilibrium point, where these forces balance. Next, we introduce key economic measures: consumer willingness to spend, consumer expenditure, and consumer surplus. Using integral calculus, we explain how these concepts are quantified and how they interrelate, providing insight into consumer dec...
(IS09) Consistency and Sufficiency
Просмотров 1,1 тыс.28 дней назад
This video revisits these foundational ideas, starting with a review of unbiasedness and efficiency, alongside a discussion on Fisher information and the Cramer-Rao lower bound-a pivotal theorem in estimation theory that sets the minimal variance bound for unbiased estimators. We then shift our focus to the main theme of the video-consistency of estimators, discussing both weak and strong forms...
(IS49) Support Vector Machines
Просмотров 1,2 тыс.Месяц назад
We start off by revisiting the method to calculate perpendicular distances of points to hyperplanes-an essential mathematical foundation for understanding SVMs. We then explore the concept of separability in binary classifiers to set the stage for introducing Support Vector Machines. Learn how SVMs work to find the optimal hyperplane that maximizes the margin between the closest points of each ...
(IS48) Decision Trees and Random Forests
Просмотров 6 тыс.Месяц назад
Starting with the basics, we introduce what decision trees are and how they can be used to make predictions and classify data. Learn how to build and analyze decision trees using measures like Gini impurity, Shannon entropy, and information gain, which help in choosing the best splits based on data purity. We then explore the effects of different hierarchies of predictors on the performance and...
(IP04) The F Distribution
Просмотров 3,6 тыс.2 месяца назад
This video, part of our intermediate probability series, dives into the derivation of the F-distribution and its critical role in statistical testing, particularly in ANOVA (Analysis of Variance) and regression analysis. We begin by defining the F-distribution, followed by a step-by-step derivation showing how it arises from the ratio of two chi-squared distributions, each scaled by their degre...
(IP03) The T Distribution
Просмотров 1,1 тыс.2 месяца назад
This video follows the structure of our previous session on the chi-squared distribution, beginning with a definition of the T-distribution and its development from the normal distribution under specific conditions. We'll derive the probability density function of the T-distribution, discussing its properties such as degrees of freedom and how they influence the shape of the distribution curve....
(IP02) The Chi-Squared Distribution
Просмотров 1,2 тыс.2 месяца назад
We start by defining the chi-squared distribution and then move on to derive its probability density function, showcasing the mathematical foundations behind this critical statistical tool. This video also highlights the key properties of the chi-squared distribution, such as its variance, skewness, and kurtosis, and explains their practical implications in hypothesis testing and data analysis....
(CA10) Integration in C
Просмотров 6 тыс.5 месяцев назад
This session starts by discussing the parametrization of paths in the complex plane, specifically focusing on lines and circles, which are foundational for understanding complex path integrals. We'll bridge concepts from multivariable real-variable calculus, particularly line integration of vector fields, to set the stage for integrating complex-variable functions along smooth paths. Dive into ...
(MC16) Green's Theorem
Просмотров 1,1 тыс.5 месяцев назад
This session begins with a review of line integrals of vector fields, emphasizing how integrals over conservative fields depend solely on their endpoints. We then explore a pivotal concept: for conservative vector fields, the line integral over any closed path equals zero. This understanding paves the way to discuss how line integrals over closed contours can be related to the area they enclose...
(MC15) Line Integration
Просмотров 1 тыс.5 месяцев назад
This video revisits the concept of integration in multiple variables, focusing specifically on line integrals of both scalar functions and vector fields. We'll explore how to perform line integrals, demonstrating the process through detailed examples that involve calculating the integral along a curve or path in a field. The session will differentiate between the line integrals of scalar functi...
(CA06) Limits and Continuity in C
Просмотров 2,1 тыс.6 месяцев назад
(CA06) Limits and Continuity in C
(IS06) Method-of-Moments Estimation
Просмотров 1,6 тыс.6 месяцев назад
(IS06) Method-of-Moments Estimation
(IC08) Fisher Information and Efficiency
Просмотров 3,9 тыс.7 месяцев назад
(IC08) Fisher Information and Efficiency
(MC13) Vector Function Fundamentals
Просмотров 1,5 тыс.7 месяцев назад
(MC13) Vector Function Fundamentals
(IS07) Maximum Likelihood Estimation
Просмотров 1,2 тыс.7 месяцев назад
(IS07) Maximum Likelihood Estimation
(RA27) Sigma Algebras and Probability
Просмотров 1,1 тыс.7 месяцев назад
(RA27) Sigma Algebras and Probability
Se fosse traduzido ficaria melhor a compreensão da msg😂
Creo que RUclips permite traducir automáticamente los subtítulos. Puedes intentar usar esta función =)
Abbreviations for orthogonal polynomials are P_{n}(x) , Legendre polynomial L_{n}(x) , Laguerre polynomial H_{n}(x) , Hermite polynomial T_{n}(x) , Chebyshev polynomial Why for Legendre and Chebyshev equation we cannot have |x| <=1 Legendre and Chebyshev equations can be reduced to hypergeometric equation Once I tried to find polynomial solution of Legendre and Chebyshev equations satisfying condition y(1) = 1 i encountered some problems From series expansion I didn't get information that c_{n-1} = 0 I dont know how to calculate sum which appeared atfer y(1)=1 condition Moreover for Chebyshev equation something went wrong that solution is incorrect for n=0
Not a big fan of those abbreviations, and also even within those abbreviations, the definitions are often different among math, physics, engineering, and other communities (I try not to get hung up on semantics). In terms of the domain of definition, it often comes down to convergence type (pointwise v. uniform v. etc) and stability of the solution (unconditional stable v. conditional stable v. unstable) and the phase plane behavior.
But suppose that in Chebyshev or Legendre equations we are interested in polynomial solution satisfying condition y(1) = 1 This will lead us to sums which I don't know how to calculate
When you say "sums you don't know how to calculate", do you mean that you don't know if they converge, or ones that you don't know if it converges to? If the former, the calc tests (comparison, dominated convergence, etc.) can be used. If the later, the probability that a random series converges to a number that one can represent is 0 (almost never); this is a result of the denseness and complexity of the transcendentals in the reals. Although once you introduce special functions (like poly-logarithms and such), you can of course "represent" the solutions more often than sticking with the original "elementary" function sets.
In the line 49 for pie chart, why we need to use "labels=cbind(favcol, " ", labpercents)" and why not directly use "labels=favcol"?
Moreso a matter of preference. One could just label with the color label only, but some people also want the percentage, the sub sample size, or potentially other information on their graph.
@16:30 you change the -5 to a -2 in the composition of the function. I think you were right the first time and it should be a -5.
Oh, yes! I second guessed myself, got lost in the moment. Good catch!
I love the intro music to these videos. It makes me feel like I'm going on a grand adventure into the unknown.
Math can be quite an adventure! Sometimes scary and intimidating like a dragon, but quite rewarding when we make it to a goal =)
Isn't the parabola at x = 3 a shifted version of y-axis symmetry, not x-axis symmetry?
The parabola y = (x-3)^2 will have symmetry about the lime x = 3, which is a horizontal shifted x = 0, and can be viewed as a shifted y axis, yes. Note a lot of teachers and books will still refer to this as not having x, y, or origin symmetry (sadly), but I think for the long term view of math, making a relation be symmetric about curves is a useful perspective, and comes especially in handy with physics and probability later on.
Why would you simplify the math in your head when you are trying to teach something and not say that when doing the first tie rank?
I mention that the tied rank is the average of the ranks they span. Since I only have duplicates, then it's just the median of the two, so usually I assume that is simple by the time we mention non parametric tests. For more than two, it would still be the average. For example, if a number has ranks spanning positions 5,6,7,8,9, the all five of the numbers get a rank of 7. Since the set of consecutive ranks is always consecutive integers, the tied rank (the average) will (also) always be the median of the data set, so not much mental math (once comfortable with median calculations); this is one advantage of working with discrete uniform distributions. I try to use previous courses as prereqs, else the video length will go beyond an hour if the calculation is drawn out. By this stage, most will usually be using R, Python, or Excel for calculations, especially once you have a data set that is in the hundreds or more. But to recap, the mean and median of a discrete uniform data set are always equal, so we can rapidly get the tied rank by calculating the median. Ex1) 1 2 3 4 5 6 7 will each map to 4 Ex2) 1 2 3 4 5 6 will each map to 3.5
nice music, thank you
Thank you =) quite peaceful~
Hello Sir, I have a PhD interview in the field of fractional calculus and I'm reaching out for guidance. I recently learned about this subject through your video lectures, which I found to be engaging and easy to understand. However, I'm unsure about the types of questions that are typically asked in this field. Could you please suggest some basic to advanced questions related to fractional calculus? This would be incredibly helpful for my interview preparation. I appreciate your time and look forward to your response. Thank you, Sir.
Be familiar with various types of operators and their properties. Be able to answer questions about their boundedness, continuity, smoothness, invertibility, behavior at singularities, behavior at 0, and what their associated eigenfunctions are. Numerical approximation of them is also a plus.
Thank you sir
Thank you for your efforts. It would assist me, and I suspect others however, if you typed rather then hand write. Now, I'm an author and I struggle to understand my own scrawl so don't take this as a scathing comment, rather helpful hint. 🙂
Hello =) Thank you for your feedback. I definitely understand your point. Reading from a .ppt (or something similar) is something I personally don't like (bad experiences from my education experience), but your recommendation does give me an idea that I may try out in the winter and see how I feel with it. Side note: back when I first started, I was writing on a glass tablet, and the handwriting was much worse 😅 but I've noticed that it depends on the app I use also; so definitely will work on an improvement strategy. Much appreciated though =)
That is a nice explanation. I wish you could show us how to implement it in R, including when there are gaps and mixtures in the data.
Definitely on my list of things to add in the coming months =) hope you are doing well.
8:15 isn't Gamma(2) =1 thereby causing the 1/2 out in front of the integral for the negative 2nd order derivative to be incorrect? whoops just saw you corrected it later haha
Yes, indeed.
I have a question about the additive property you were talking about around 4:15. Even though for polynomials the derivatives come out to both be 1, since in the additive portion of the fractional derivatives you end up dealing with \sqrt{x}, do the derivatives have the same domain?
Great question. When it comes to domain, it honestly depends on what you allow and accept, but the surface level answer is no, they won't have the same domain, but they can if you allow domain extensions and analytic continuations in the transformations. But a more interesting point is that depending on how you approach a particular derivative (in the order sense), you could technically approach a "different function", with the domain being the first thing in question to be different.
4:48 did you mean to write the fractional derivative = \frac{\Gamma(n+1)}{\Gamma(n+1-\alpha)}x^{n-\alpha}? The one I saw on screen still has the k in the denominator
Correct ^_^
Note: At 32:04, the correlation is not unbiased for the population correlation (although it is asymptotically unbiased).
I’m starting my second playlist, and I want to say: great work, good explanation! Thanks a lot. Please continue with this channel!!
Thank you so much! Comments like these help motivate me to continue trying to better the content I enjoy sharing with others. I've recently been on a break, but plan to push out a few months of content a couple weeks later, just currently deciding which topics to include. If you have a recommendations of things you would like to see, feel free to reach out and let me know!
This is an interesting video! Thank you!
You're very welcome =) hope you are doing well.
At 13m17sec the right answer for W(0) should be 0 and not 1 , right?
Yea, that's correct, W(0) = 0 :)
Thank you for the video. What the application you use in whriting ?
Currently, Microsoft OneNote :)
u forgot the family wise
Yea, family wise is alright. But it's nothing compared to what Bonferroni's got.
You are an excelent teacher. Thank you very much in your clear presentation of ideas. I have a small doubt. In 8:10 you stated the reflexive property somewhat different of the definition. A relation R on a set S, R⊆S×S is reflexive if and only if for all x∈S we have that xRx. The if and only if statement in your definition is always true since it adresses the definition of aRb notation. In the sense that (aRb) is a shorthand of (a,b)∈R. So xRx if and only if (x,x)∈R si indeed always true but not the definition of the reflexive property.
Thank you for your kind words! And yes, you are correct. Retrospectively, I would prefer to say that a relation R is reflexive, provided that for any x chosen from S, (x,x) must belong to R; perhaps this is a safer way.
thanks so much sir!!!!!
Thank you ^_^
thank you so much!!
Thank you :) let me know if there is anything you have curiosities about or questions!
Amazing. Very clear, keep up the good work!
Thank you =) hope you are doing well. Feel free to let me know if you have any questions!
Same as usual, amazing video quality. I just want to add on (if I am wrong correct me), the fisher information can also be defined as the expectation of the square of the first derivative of the log-likelihood function, as I found it more intuitive to understand it that way. The first derivative accounts for the change in probability, summing up and averaging them essentially tells u how drastic there is a change in probability through the change in the random variable given a set parameter (which is something I found relatable to Shannon). The power term prevents offsetting from negative changes.
Thank you four kind words =) and yes, some will define fisher in terms of what you mention, which becomes intuitive once one develops a geometric sense of what we are doing. Shannon entropy (and other measures like KL divergence) also closely relates to these mechanisms also, but hope to investigate these at a later time when I get the chance. Hope you are well!
With the amount of effort you put, I really wish your channel gets more popular!
Thank you! Maybe one day =) For now, I just enjoy making content even just for one person to help at a time
Desperately waiting for FC05 !
Will try to have new ones in the month of July =)
Unstoppable, watching 3rd video in a row
Thank you =)
Note: At 12:32, it should read [messed up my fractions :( ] (sa^2/sb^2) * (sigb^2/siga^2). Though if you prefer the one written, you could do with respect to a F(vb, va) distribution instead of an F(va, vb) distribution.
At 12:31, shouldn't it be (S_A^2/S_B^2 )* (sigma^2_b/sigma^2_a)?
Yes! Thank you for point this out. I've pinned a comment above with a correction (two possible ways to correct, one being the one you mentioned).
measure theory up ahead 🫡 💃
Possibly ^_^
Note that for the extrema at the origin, being a max or a min depends on direction, as one can dind its a saddle for the surface (unless you restrict the domain).
my goodness, excellent explanation thank you very much can we compare graphs of Euler's scheme and Rk4 scheme for system of differential equations
Thanks for your kind words :) Technically yes, but a bit more complex since we usually look at phase portraits of 2d or higher for their solutions, but we can look at each individual variable over time for both solutions; that is if we have an x' = ... y' = ... system, solve using both methods graph x v. t and y v. t for both methods to compare solutions; if the time graph comparisons are similar, then the corresponding phase portraits will be similiar; this will also work for systems with 3 or more equations also.
Hi! What is the interval of convergence of digamma function?
Digamma is defined (at the least) on the positive reals. Extensions can be made on a larger subset of C though, just like the gamma function :)
thank you for making these videos :)
Thank you :) feel free to let me know if there are any topics you want to see or if you have any feedback so that I can better help your learning journey!
i am begging bro to calibrate his drawing tablet
Hello :) what I've realized actually is the app I'm drawing in (onenote) and the tablet I have aren't ideally compatible. I haven't yet found a drawing app to replace it yet, but if you have any recommendations, would love to hear. Thank you for the feedback though.
1,999th view xd
A great number for a great person ^_^
When reindexing takes place at 9:32, why is only one of the l’s in the function being summed over replaced with l-1? I can image how it might not matter in the h goes to zero limit, but it isn’t mentioned here.
Great question. In short its a transformation of coordinates from polynomial to exponential to polynomial with two u-substitutions between; I omitted here since it would add a bit more time than I wanted, but I think exploring different ways to get to the end result is just as magical, as long as (as you mention) things converge in the same way (pointwisely at the least) as h tends to 0.
@@LetsLearnNemo Intersting. Thanks for the feedback. I'll try playing around with potential transformations. BTW, your videos on fractional calculus are the best I've found, by far!
Thank you so much :) I've been meaning to add and update the series but have been to busy, but this summer I have some definitive additions I plan to add. So I'm excited about that
The divisibility rules of the 1st 10 powers of 7 7: The difference between twice the last digit and the rest of the number is a multiple of 7 49: The sum of 5 times the last digit and the rest of the number is a multiple of 49 343: The sum of 103 times the last digit and the rest of the number is a multiple of 343 2,401: The difference between 240 times the last digit and the rest of the number is a multiple of 2,401 16,807: The difference between 5,042 times the last digit and the rest of the number is a multiple of 16,807 117,649: The sum of 11,765 times the last digit and the rest of the number is a multiple of 117,649 823,543: The sum of 247,063 times the last digit and the rest of the number is a multiple of 823,543 5,764,801: The difference between 576,480 times the last digit and the rest of the number is a multiple of 5,764,801 40,353,607: The difference between 12,106,082 times the last digit and the rest of the number is a multiple of 40,353,607 282,475,249: The sum of 28,247,525 times the last digit and the rest of the number is a multiple of 282,475,249
Great, now prove DCT xd
You mean the dominated convergence theorem? :) I leave most theory + proof things for real analysis, but yea DCT is amazing. Triangle inequality and/or Cauchy-Schwartz makes it a bit more easier though.
thank you nemo
Thank you :)
No offense but I don't really understand why it's a major discovery. Rules where you can sum a certain number of times the last digit with the rest of the number always works because of a number that ends in 9. Although now that I think of it 3 years ago I got surprised when I discovered the divisibility rule of 41 by myself but I wasn't completely sure if somebody else had figured it out before
It's moreso an awareness type of thing and sharing your realization with others. Sometimes things get lost in history for a variety of reasons with lack of interest being one of them, then later people are interested again. So although not a major discovery per se, but an interesting and potentially useful result, just like your 41 divisibility rule :)
@@LetsLearnNemo I discovered to identify a multiple of 41 you can substract 4 times the last digit by the rest of the number
That's pretty neat. I find it interesting that divisibility by (a lot of, maybe all?) primes can be equivalent to divisibility by shifts of primes (composites).
@@LetsLearnNemo usually divisibility rules of prime numbers that end in 1 require substracting the last digit by the rest of the number
@@matiaspereira9382 This is super neat actually. Number theory has quite a few results I find quite fascinating!
may i ask where you put the solutions for the question at the end of each video? thanks
Hello :) At the moment, I do not have an answer bank built for the eov questions, but do plan on having it built sometime later this year.
Will there be more time series videos soon? I'm kind of struggling and your videos are always helpful
I plan to, yes, in terms of release times, I'm not sure. But possible two more time series vids across April :)
This video deserves more views
Thank you for your kind words :) Helping a lot of people is my goal, but just helping a few people is still okay for me :) Feel free to reach out if there are any topics you would like to see or need help on~
great video keep up the good work man
Thank you :) Hope you are doing well!
Great video! This is super helpful for a problem I'm investigating at the moment and the way you go through with examples is really helpful! One question if I may, I'm doing a personal project and I have a dataset with a huge number of groups (about 1000), and a lot of samples in each group (about 200-300). I'm trying to identify which groups are meaningfully different to the general population. KW says there are some differences between the groups, but I'm unsure how to go about actually identifying them, would it be valid to use CI to compare each group to all the values not in that group, doing pairwise between every group feels infeasible a) because it's a huge number of comparisons and b) it still leaves me with hundreds of p values for each group
Hello! So if KW states there is some difference but pairwise isn't practical for large g (say 1000), partition into smaller sets, say 5 sets of 200, do KW on each set of 200. Let's say that only 1 set of 200 let's KW reject equality; then you can do pairwise on the 200 rather than the total 1000. Note that the partitions need to be chosen at random. This is one way around it :)
At time 43:12, it should be sum(SR^4), not sum(SR^2). From here, the rest is correct.
At 10:48, it should read: due = alpha*immediate immediate = nu*due Proof: a[n:i] = v + v^2 + ... + v^n ä[n:i] = 1 + v + ... + v^(n-1) so v * ä[n:i] = v(1 + v + ... + v^(n-1)) = v + v^2 + ... + v^n = a[n:i]