Відео

I'm trying to study for a test but I feel like all your videos are using wolfram - a program that a student cannot use or have access to during an exam. It passes over a lot of the "How To" aspect. I know it's messy, but that's what is required of students to know, understand, and perform.

I do not get how Beta comes to be in that tail. Please guide.

Thank you so much

Great Video! Thank you for sharing this elegant proof! Ignore all these trolls in the comments

Thank you sir

Usefull video for cfa

The only video I could find that eplains how to logically come up with the formula. THANKS

Thanks bud, really appreciate your excellent work!!

Stop Orgasm

Thank You very much, I have been working on this in my head lately. The other terms of the Poisson are very intuitive (Lambda ^r in numerator which is multiplying mutually exclusive probabilities and r! In denominator which is changing permutation to combinations since order doesnt matter, but the term e-^lambda is a little sticky...but it is essentially the portion of all the "non events" over the interval, where the interval of non events must scale with the "intervals" of the "r" events.

Thank you for the video, can you help me how to prove that is unbiased in this question? Question: Compare the average height of employees in Google with the average height in the United States, do you think it is an unbiased estimate? If not, how to prove it is not matched?

Are you alive?

This reaaaaaaaaaallyyyyyy helped!!!!!!!!...thank youuuuuu ❤️

Nice, just what I needed. Thanks!

Went way too fast to explain anything in any detail. Slow down next time, and explain each equation thoroughly. Also, solving the equation manually would help the understanding of what is happening and also help someone that needs to take a test on this.

Man this algebraic explanation of square deviations as quadratic equation was completely mind-blowing thing, instead of just taking derivative and equalizing it to zero, you simply solved quadratic equation. That was a great eureka moment for me. Thank you so much man!!! Subbed

Why are you out of breath? Seems like a pretty strenuous calculation lol

You are wrong, s squared equal to 1 over (n-1) times the rest of your aquation

Great Video!

m.ua-cam.com/users/results?search_query=rbs+mathletics

Very good my man, very good!

Thank you very much for the thorough explanation! In the book that I am reading this bias is given without proof and with comment "it is straightforward to show that...". Well, I do not think that its is straightforward and almost exploded my head trying to prove this :D

thank you!

Thank you. This was what I looking for

really helped me thanks :)

감사함니다 ^^

Thanks! This is the best example for explaining MLE of uniformly distributed values on UA-cam I have ever seen.

Best one Ive found

marry me

Great explanation... at the end we could have simply find derivative of the sum wrt mu and equate it to zero to find MLE of mu = x-bar

doesnt make sense, trying to maximise but choose the value that minimises?

Thank You !!

What is the best way to make mle unbiased? Isn't there something better than making a correction via N-1 instead of N??

Clearest example I've seen on UA-cam, thank you!

Find UMVUE of the mean of a normal distribution whose standard deviation is one pls give me the answer for that

good video but his breathing is so much irritating

Did you just run a marathon ?

You are my hero. Thank you!

Thanks for the visualisation I understand it now, amazing video keep it up

like it, it actually solved my microeconomic lemon market question! thanks!

One thing that bothers me in math classes is when they put up a symbol and don't explain what it's for. What is "a"? I'm assuming it's not the same as alpha... bc that would be saying that the null hypothesis would be the average of the entire population equals the probability of making a type I error. Which makes absolutely no sense.

Nice Going through derivations are much better than memorizing the formula

When I apply this method based on CLT to my case (n=30, successes=29), I get: the μ estimate = 29/30 ≈ 0.967, unbiased SD ≈ 0.183, SEM ≈ 0.183/(30^0.5) ≈ 0.033, (z-statistic, i.e., narrower) 95% CI of μ = 0.901-1.032, and the probability of μ >1.000 equal to ~15.9%. Are you sure the CLT is good for the random variables with distributions defined over a limited array (or range) of values?

Thank you. It helped me solve my problem.

why not just take dL/d mu = 0

One question: at 5:04 or so he says we can add the powers, but then writes a minus sign for all the powers of e. What am I missing?

idiot

thank you!!!

Can someone give this mans a glass of water god damn swallowing like he stuck in the Sahara desert

very helpful. Thanks 👍👌