Introduction to power in significance tests | AP Statistics | Khan Academy

Introduction to power in significance tests.

AP Statistics on Khan Academy: Meet one of our writers for AP¨_ Statistics, Jeff. A former high school teacher for 10 years in Kalamazoo, Michigan, Jeff taught Algebra 1, Geometry, Algebra 2, Introductory Statistics, and AP¨_ Statistics. Today he's hard at work creating new exercises and articles for AP¨_ Statistics.

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[simba]

Finally, as a beginner, I can understand why the significance threshold increases, would cause the power increase. Thank you for sharing this super clear explanation!

[lindajohnsen]

I have seen so many videos on this in german and now decided to watch an english one and this one just taught me everything I needed to know in less than 10 minutes <3

[delcapslock]

I think the vocabulary gets in the way of explaining power. In general what is missing is an intuitive explanation preceding all the Type I/II error, effect size, alpha, etc. Like, "power is how we quantify the likelihood that your sample has all the properties of the population", with some illustrations.

[nielsvandestolpe]

Very clear explanation and too the point. Thank you

[therapistinsights]

7:46 by increasing a, the type 2 error increases not the type 1 error.

[tuber]

Perhaps this is pedantic, but 1 - P(type II error) isn't exactly the same thing as P(not making a type II error) -- it's more like P(not making a type II error | H0 false). For example, if H0 is true, then we _can't_ make a type II error, but it shouldn't be included in this probability.

[matthewmckendree]

I am doing summer homework rn and this is so helpful.

[kyubeenkim]

Thank you so so much, I finally understood what this is

[nhackim]

You try to give the video more brightness it will be great if you do

[wenwensi]

8:00 increase sample size will not change the distribution curve, the description is so misleading.

[AshutoshMishra-boic]

this is called "Power" of Khan academy

[Killahschinken]

Doesn't the probability of not making a Type II error (1:50) consist of all 3 other possible cases - i.e. also the probability of making a Type I error and correctly failing to reject the null hypothesis? Shouldn't it be P(not making Type II error | H0 is false)?

[tonyteja]

We wish to test H₁ = 100 against H₁100 using a sample of size n = 16 from a n (u; ²) distribution. Suppose that we know that the true mean is μ = 100 + 20. (i) What will the power of the test be if we test at the 5% level of significance?

[gooddeedsleadto]

8:15
Explained really excellent, but the sketch is not clear
Thank u
May be because I am watching the video on a relatively smaller screen (iPhone Pro max 15) instead of larger screen.
The Alpha goes up power goes on the sketch is not clear.

[rubensasson]

thank you so so so much for this video !

[gooddeedsleadto]

Thanks great video power concept.
Couldn’t u also explain p value concept, With height & heads & tails examples
Why p value is preferred over critical value & z or t statistic in hypothesis testing? or why use p value?
Does it say or determine the actual probability is of lesser significance to reject the belief about the population parameter or mean? Is this the reason p value method is valuable & more reliable?
Thanks 😊
😊

[chessandmathguy]

great video! would it be possible to add it to the AP Stats portion of Khan Academy? Thanks.

[vedantsahu]

Make a video about Componendo and Dividendo

[boxerbomber]

This has to be one of the most confusing things ever

[Dekii]

So, I guess I am the only one who still doesn't understand what the power is after watching this video... Gosh why am I even studying stats for, I am just not built for it!