The Essential Guide To Hypothesis Testing | VNT #12

A (mostly) non-technical on using and talking about hypothesis tests in your work

OTHER CHANNEL LINKS

[desktus]

My god man at this point you should do this full time. You have a gift. The content and presentation is arguably immaculate. I am trying to learn statistics, but so often it is assumed that the learner is intuitively familiar with some statistical/mathematical principles and they are not accurately explained. For example when I try to learn what a standard error is many talk about how to calculate the standard error of the mean and not about the concept of it. Likewise the mathematical notation is all over the place. Can you tell me why regression models represented as equations are often writte like so : yi = b1*xi + b0 + ε and not like so Y = beta0 +beta1 * X + Ε . I believe using the small letters and having a index indicates that we use realizations for the random variable Y or X for observation i. But that does not accurately illustrate the general model in my opinion. Iam so confused why it is so widespread.

[RomanNumural]

I'm also a PhD student (math finance which is mostly statistics) but my background is applied math. Your videos have been very helpful for filling in my knowledge gaps that an undergrad in stats might learn! Thank you!

[CharlesLampman]

The past half year has been my sprint into grad school prep with an emphasis in ecological modeling- lots of time spent in R and side quests to more fully grasp statistical intuition. You have continued to fuel the fire with these easy to understand, well thought out videos. I hope this gets a 1/10!

[xTurqoise]

I'm currently writing my master thesis in CS and this video is an excellent refresher of my statistics class!
Great video! Thanks!

[dan_pal]

This was amazing, I’ve never seen the p-value being explained that clearly.

[xanmos]

Thanks a lot for this video.
I’ll share this to my students by posting in our Canvas LMS. :)

[EffigyOfficial]

Couldn't have come at a better time, I've just started studying this

[schrodingersalphacat]

Awesome video. While in university, I struggled a lot to understand the meaning of the p-value aside from its "straightforward" definition as a conditional probability. The way you phrase your results at the end makes things so much clearer.

[barronwill]

great video, interesting perspective to see the problem

[onlyonecjb]

Fabulous video. Thank you very much for the clear explanation. Will now check out your other videos as well.

[tylernardone]

Someday I hope you do a video on fixed and random effects and mixed models. I think you may be the only man alive that can help me understand those clearly 😂

[weitzun]

This is a golden masterpiece! No doubt to subscribe. Thank you!

[bicepjai]

My suggestion would be to communicate (video time: 14:44) the population parameter range in CI rather than the test statistics range. Great videos and keep up the good work.

[ControlAlpha]

terrific video!want to know more about multiple hypothesis.

[keepfeatherinitbrothaaaa]

This was very good and clearly communicated. I would have liked only some more detail on calculating the confidence intervals and maybe a step by step solution on a concrete example

[Mystic]

Omg you’re the goat, I have a review quiz on hypothesis testing this week

[matteofrattini]

You rightly said that seeing a p-value alone should always make you wonder what the null hypothesis was, so wouldn't it be better if we presented the result in the order:
1) Null hypothesis
2) Test results
3) CI and p-value
4) Conclusion
?

[orpheus]

Would you consider making a video on a suggested topic? Regression analysis, given how inportant it is to many fields including decision-making.

[RepChris]

I dont think a Chi² test is the appropriate test for the coinflip, since its a very simple experiment with only two possible results (heads or tails), meaning a binomial test is much more appropriate. Since it makes more assumptions it should also be able to reject the null hypothesis with less data.
Its also worth noting that the sample size is quite literally on the border of what you can (at least by common agreement) properly use the Chi² test for (# of expected occurrences assuming H0 for all buckets >= 5 (or >= 5 for at least 80% of the buckets, and no bucket with less than 1))

[tufonkin]

I was a bit confused about p=0.026 as long as an exact probability of the observed and more extreme outcomes could be calculated mentally: all heads, all tails, 10 cases of 1 tail and 10 cases of 1 head. Total of 22 out of 2^10. Something definitely below 0.022 as long as 1024>1000. Calculator helps and gives 0.021.