Bootstrap Resampling

Great Video! I'm writing an essay on this topic and have a few questions. Firstly, I've been reading about forming an empirical distribution from the sample data, would this just be done in the step when sampling with replacement from the sample data is undertaken? Also say if N=10 for instance and then you let B=10,000 then surely your bootstrap resamples will repeat? Is this allowed or is there a limit on B dependant upon N? If you could help it would be appreciated :)

Thanks for the comment. Yes, you are right that you form the empirical distribution just by sampling with replacement. And in the case of N=10, B=10000, the bootstrap samples will definitely start to repeat. This just means your resampled statistics should converge once B becomes large enough. So, the error in the bootstrap resampled statistic will be limited just by the small N size.

Can bootstrapping be used in point estimation of the sample parameters?

hello great video. i will be using this technique in my study . i hope you can help me with more references and videos that i can refer to in order to understand this test more~

You will make a wonderful teacher.

please help me to solve this question Bootstrap resampling is a way to get the most out of a limited amount of data for model estimation or validation. Given a random walk model x1 = ε1, xt = xt−1 + εt, t > 1, where xt is the observation and εt is the noise at time point t, and data sample 6, 1, 3, 7, 12, 6, 19, 29, 5, −6, −9, −29, −11, −13, −5, generated from the model, describe how to generate more data from this sample using bootstrap resampling.

Hi, thanks for great explanation. Can you say something about how to get the x* vector from the original x?

it was very helpful kindly upload some more

We got the method. The question is what is the mathematical validity, that the result from bootstrapping have any statistical significance. 

Thanks for the vid, the very last slide was quite helpful. I find it quite amazing that you can infer something about the original population by resampling from an already small sample!

thank you. very clear explanation. very helpful. :)

Thanks very much, I'm studying statistics at the moment, and asked a lecturer about bootstrapping today. This was a lot more clear and lucid than his explanation. I'm really impressed by this technique; I had figured as it is evidently powerful, it would be difficult to implement, but I can already think of the code. Thanks again

Very clear explanation. Thank you!

thanks, I had to learn this while learning about molecular cladistics and it helped a lot.

very good video thank you

Hmm.. but doesn't the central limit theorem apply to the mean statistic? If I take N resamples and calculate the mean I should get a normal distribution. But if I take N resamples and calculate the mode, I might not get a normal distribution, right?

sort of got the idea, but the speech was so hard to follow. Thanks though.

Not sure it's proper to shade under and below the cdf curve - I think the boundaries would be marked at the values of x where cdf(x) = 0.025 and cdf(x) = 0.975. Graphically, this is a dotted lines from 0.025 and 0.975 on Y-axis running horizontal to the function, then straight down to the corresponding X values on the X-Axis

Which Technic is better, bootstrap sampling and sample random sampling

you picking those samples at 1 minute, at a rate slower than a toddler can think of numbers, made me want to punch a wall.

Have you covered Jackknifing method before? I just want to compare differences.

Very, very good video. Really.

Sounds like your computer is going to take off!

Hi, how many bootstrap distribution do you recommend for a sample of 360?

Thanks!
P.S. Speed: 1.25 for human experience.

When you mention Gaussian distribution due to central limit theorem, isn't it when B is large not when N is large?

Hey man, you did explained the concept very clearly. However, you gotta put more energy and enthusiast. You sounded like if you don't fully understand the concept and was talking with extreme care not to say something innacurate, which is fine, except for the part that it sounded slow and kind of boring. Gotta put more energy!!!

2X looks fine too.. and people who are watching this should be thanking him.. he didn't made it for people who already know it.. its more for those who is just trying to gain insight.. saying slowly takes time and allows people who are listening to gain a better insight .. so please just increase the speed if you people don't like the speed of the video.
bottom line : Either post constructive comments or move on. its for learning not commercial..

How many possible bootstrap samples are there from a data set of size N?

Please, some material about gibbs sampling? I need it so much.

I just want to say you teach better than my prof!

Thanks for your video!!
I have a question. If I want to estimate the t-statistic of one parameter in, for example, an OLS estimation with a small sample, the procedure is the same?