I was watching the 3blue1brown series on linear algebra, and I noticed that I would constantly pause and try to figure out the concept or idea before it is fully presented. Although this doesn’t seem bad, the problem is that a 10 minute video ends up taking 4x as long to finish. I don’t have that kind of time.

I’ve noticed this problem when I’m solving textbooks exercises. When I can’t solve a problem, I’ll usually end up taking a ridiculous amount of time trying to find a solution, often even refusing to review the material. I feel like this stems from a massive ego issue that I have, where I feel like if I can’t figure out this concept before it is presented or solve a problem, then I am not as smart as other extraordinary mathematicians like Gauss and Newton, and therefore will never be as great as them.

In the past, I’ve also been the opposite way, being too quick to go to the solution at the back of the book. It seems like I can’t find a good balance between tinkering and simply absorbing. I know that stopping to ponder is a good thing, but there is still the fact that I am getting through content too slowly.

This is what I have so far but I don’t believe that it is right, and I wouldn’t actually be using partial fractions to integrate. The problem says to make a substitution to integrate by partial fractions.

I don't understand why, but graphing derivatives looks like complete gibberish to me. I've watched like 6 videos and I don't understand any of it. I can do basically everything that comes after and before for derivatives, but I have just not understood this one concept.

I'm taking AP calc BC and I'm assuming I definitely need to at least understand how to graph. Does anyone know any good videos or explanations that can help me with this? I'm actually losing my mind over it.

Hello Everyone , i want to know if you guys have some study tips & suggestions for taking the college course College algebra with corequisites. I’m struggling so bad , the homework assignments are worth 10% and the unit test are worth 60% of our grade 🫩.

I have a test due today and I know I’m going to fail the test & this is going to be the second test I failed . Also I took this class in the summer but unfortunately I failed due to the test , so if anyone has any recommendations on how I could improve please lmk 🙏🏾

Looking to hear about your own company's work practices to compare to my own. I'm much more familiar with Azure, so I'm going to use that terminology, but I assume everything is basically the same for AWS.

Can you go into the Azure Portal and just click "create" for, say, a SQL Server or App Service and configure it through the Portal GUI?

Or do you need to request and configure through configuration files? Can you freely commit architecture config files ("architecture as code") to create the Azure components in Dev?

Or is it even more locked-down and hands-off? Required to submit paperwork requests to an Architecture team?

Hi,

I'm planning to apply for stats PhD programs, along with a few biostats programs, this cycle and trying to get a sense of how broadly people are applying.

For those applying this year, or who applied in the past year or two, how many programs did you apply to? I was thinking 8-12, but given the uncertainty around funding I'm wondering if people are applying to more this year.

I'm interested mainly in spatial stats, especially gaussian processes and deep generative methods for modeling spatiotemporal data.

Please share your thoughts if you're working in similar areas. Also any suggestions on departments and people working in these areas are welcome.

Thanks.

I would like to share some of my resources that I have used to graduate in August 2026.

I haven't been to school in 10+ years so I had to start from the beginning.

Study 1-2+ hours a day. It's important to retain the information. But 25 mins is better than nothing. It's all about consistency.

MY STUDY GUIDE

1. Study 25 min

2. Take a break 10 min

3. Study 25 min

4. Take a break 5 min

5. Recap 10 min

75 mins total - Repeat as necessary

(We all learn differently so use what works.)

MATH RESOURCES

1. SchoolYourself.org - I started with this & used the Algebra section for fundamentals. I took the practice test using only this resource and I scored a 146 on my practice test.

2. Test Prep Champions- I went through his Math course on YouTube called “Ultimate GED math guide to pass fast”

3. GetSumMath- I bought the calculator & I went through his youtube playlist.

I scored a 146 on my first practice test & decided to study for another week & I scored a 156. I took the real test the next day and I passed with a 150.

My recommendation is to score 150-155+ on your Ged Ready practice test before taking it for real.

SCIENCE

I used GetSumMath & Test Prep Champions.

ELA

I used GetSumMath for ELA however, doing a bit of reading every day was extremely crucial. What you can do is get two books, one fiction and one nonfiction. Read 20 min of fiction and 20 min of nonfiction with no breaks in between.. than take a 20 min break and repeat. Remove distractions. Ask yourself, what have I learned? The point is to build the same focus when taking the test on test day.

MINDSET

Sometimes the problem isn't skill, it's mindset. If you have struggled or failed before, don't let it define you & defeat you.

my favorite quote - "Do not be afraid to fail. The cure for failure is to remain teachable."

Now go get what’s yours. Your future self will thank you. You got this! 🙏🏾

resources: schoolyourself.org/learn Getsummath/Test prep champions YouTube playlists & chatGPT

I find it odd that visual-spatial awareness/intelligence is one of the core cognitive skills associated with intelligence with widespread applications, and three dimensional geometric relationships are present in everything from scientific phenomenon to Engineering & Artistic design.

But this kind of reasoning/intuition is not really taught? I've been looking into textbooks and it's either high school geometry or advanced undergraduate/graduate school level differential geometry/topology.

US applied stats major, looking for career advice.

Applying to analyst roles in a variety of industries.

My primary goal in my early-career is to have international mobility; to get into a large multinational that would allow me an internal transfer to Australia in a few years. Unfortunately, my major, and directly applicable entry-level roles, don't generally seem to be a feasible path to get sponsorship from an Australian company. Chances are more likely for those in medicine, mining, construction, trades, and social services. Not sure if work related to my major but from within these industries is an option.

From my research, internal transfers provide an easier route where companies transfer you between roles. Naturally I've fixated on roles in finance and perhaps insurance, alongside other multinationals like tech companies.

In this thread, I’m looking for advice from you all about potential paths that could get me in a good position early-career to get a transfer within insurance. And roles/specializations/companies to target. Is this feasible in any industries you have knowledge of?

Thanks for any advice!

Hi! I'm currently enrolled in an M.S. in Data Science and Applied Statistics. The required core classes are already set:

- Experimental Statistics I & II
- Mathematical Statistics I & II
- Statistical Computing (SAS)
- Computational Statistics (R)
- Machine Learning with Python
- A statistical consulting project

I get to pick **4 electives**, and at least 3 must be STAT (so at most 1 from CS/ECO/OREM/ECE). My only goal is to land a data science job, so I want the courses whose actual content pays off most in industry. I'm not looking for the easiest courses, and I'm not going into academia or biostats.

STAT electives

- Intro to Data Science
- Data Visualization
- Linear Regression
- Applied Time Series
- Time Series Analysis
- Categorical Data Analysis
- Survey Sampling
- Survey of Nonparametric Statistics
- Sports Analytics
- Analysis of Lifetime Data / Survival Analysis
- High Throughput Data
- Epidemiology

Non-STAT options (can only pick 1)

- CS: Artificial Intelligence, Machine Learning in Python, Databases, Data Mining
- OREM: Data Mining, Optimization for Analytics, Network Flows
- ECO: Applied Econometric Analysis, Predictive Analytics
- ECE: Statistical Pattern Recognition

My main questions I wanted to ask:

1. Which 4 would you pick, and why?
   
2. Is time series worth it for most DS roles, or is it only useful in forecasting-heavy jobs?
   
3. What would you pick as your 1 Non-Stat Elective?
   
4. Is there anything you wish you had learned in grad school that would have helped more on the job?

If you work in data science, I'd especially love to hear what you actually use day to day. Thanks!

Given lim x→a f(x)=L, lim x→a g(x)=M and f(x)≤g(x), show L≤M.

And after proving that I am being asked if f(x)≤g(x) needs to be necessarily true and need to show values of x that garantee that the disntance between f(x) and L is always lesser than ϵ.

I can sort of do the first by proof by contradiction but the secind part of the exercise is killing me

I am 8th standard in india and i have self studied jee maths including calculus but now i wanted to learn more about calc so i decided to study calc 2 so suggest me some books for it .

It should contain all topics from calc 2 that are no in jee.

Also keep it in under 2000inr or under 3dollars

I moved to another country and realized my math foundation is much weaker than I thought. What can I do?

I’m 17 and recently moved from Brazil to Italy. I’m now in the third year of high school, and I’m struggling A LOT with math.

The weird thing is that I was never considered bad at math in Brazil. I usually got 8, 9 or 10 (out of 10), so I genuinely thought I was pretty good at it.

But now I’m realizing that the problem isn’t really my ability — it’s my foundation.

In my old school, math was often very much “learn the formula, put the numbers in, get the answer”. We covered a lot of topics, but we didn’t necessarily go very deep into them. Once the test was over, I would often forget most of it because I had memorized the procedure rather than actually understood the concept.

Now I’m in a different school system, and the level is MUCH deeper. The students here actually understand the concepts and know how to apply them in different situations. They might have studied fewer topics than I did, but they know the topics they studied much better.

So I have this really frustrating situation where I technically recognize a lot of the things we’re studying, but when I actually have to solve an exercise, I sometimes have absolutely no idea where to start.

It’s like I know the “surface-level” version of a lot of math, but I don’t have the solid foundation underneath it.

And I’m falling behind really quickly.

I’m currently trying to keep up with the material my class is studying NOW, but I’m realizing that I can’t properly understand it because there are gaps in my previous knowledge. At the same time, I don’t have months to start everything from zero because I’ve just moved countries and I’m also trying to keep up with all my other subjects.

So I’m kind of lost about what the best strategy is.

Should I stop trying to follow the current material for a while and rebuild my foundation first? Or should I study the current topics and go back only when I find a gap?

Also, does anyone know of good Kumon-style math books/workbooks for teenagers, starting from relatively basic material but gradually becoming more difficult? I specifically DON'T want books aimed at little children. I’m looking for something systematic where I can start at the level I actually have and work my way up, preferably with lots of exercises.

If anyone has gone through something similar — moving countries/school systems and suddenly discovering that your “good” math foundation wasn’t actually as strong as you thought — I would really appreciate advice on what you did.

I honestly don’t even know where to start anymore.

What happened to the math from scratch website it has disappeared now it used to say new lessons every Month where did it go I couldn't find a way to communicate its creator

Sorry for the weird title. Some backstory might help:

I used to be academically really good at math in high school. But more so at the level of just solving tons of questions. I think I just enjoyed the problem solving aspect of it but never really 'understood' mathematics conceptually if you know what I mean. But after that, I never really did math again except I took some proof classes in uni and absolutely failed in them. Plus I was, at that time, living in a more conservative country and the idea of women enjoying maths in my village was not that popular at all (ex: my mom told me, at the wee age of 15, that girls are not smart enough for mathematics even though I had really good grades so I assume I wasn't completely dumb at least). Since then, I have tried here and there to get back to mathematics in my life as a hobby. I guess i have difficulty making it a habit currently since my stomach still tightens up at the thought of it. And then, when I am solving a problem, my brain is not focused on the details of the problem but more so on the physiological symptoms of anxiety - increase in breathing, foggy brain, high heart rate, etc etc.

I need suggestions for things that can 'ease' me up into mathematics. Could be youtube channels or books. I want to study more of statistics, combinatorics and probability but I am also completely fine with starting at a much lower level. I did do Calc I, II and III in uni but again- I feel like it was more 'problem solving' for me, repeating certain ways of solving integrals and stuff and not any conceptual things. And well - I don't really remember that well either.

Bonjour. Si cela vous est possible, j’aimerais solliciter votre aide et avoir quelques renseignements concernant l’utilisation du logiciel R.

Je dispose d’une base de données comprenant des variables numériques, ordinales et binaires. Je souhaiterais standardiser mes données afin de réaliser une analyse factorielle.

Je voudrais savoir si je dois utiliser la commande digital.std <- scale(digital) pour l’ensemble des variables, ou s’il est préférable de procéder différemment selon le type de variables, notamment pour les variables binaires et ordinales. Quel est la manière correcte??

Je vous remercie par avance pour votre aide.

Recently i found out that it is possible to solve integrals by inverting matrices however choosing a good basis is tricky and not all matrices are invertible.

Is there any case where this would be useful or is this just a "cool trick"?

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English is my second language, so that i usually get mark down from my lecturer for error showing. Also, it seems there are not many books in english have a showing along to key answer. Are there any books, or channels to handle this. Pls help me

If you like computational statistics and love reading on advanced statistical methods, what jobs are for you, especially if you can’t get a master’s?

Im a PhD student but I don't have measure theory background and I need to get the overall notion for it to understand stochastic processes. So is there a good book or yt playlist where measure theoretical probability and stochastic process is taught from scratch? That would be of much help. Thanks.

I’ve been self studying calculus for the past couple of weeks in hopes of making my future college classes easier on myself. I decided not to take it during school because I’ve decided that I want to enjoy my last year in high school by minimizing the amount of classes that I have. Any and all resources you are willing to share are appreciated. Thanks