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zakruti.com » Knowledge, science, education » Crash Course
Playing with Power: P-Values Pt 3: Crash Course Statistics #23

Playing with Power: P-Values Pt 3: Crash Course Statistics #23

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Rating: 4.0; Vote: 1
We're going to finish up our discussion of p-values by taking a closer look at how they can get it wrong, and what we can do to minimize those errors. We'll discuss Type 1 (when we think we've detected an effect, but there actually isn't one) and Type 2 (when there was an effect we didn't see) errors and introduce statistical power - which tells us the chance of detecting an effect if there is one
Date: 2022-04-04

Comments and reviews: 10


Mistake on type I\ type II error visualizations?
I think There is a mistake in the visualization of the error types on -6: 20;
Moving the threshold ('cut-off-line') to the righter regions from the point of two of the distributions equality: while type I error is indeed the area from the threshold to the right and under the H_0 distribution,
type II error should be to the left of the threshold and under the H_1 distribution, but it is not marked that way.
(It is actually marked the area that is under both (minimum) of distributions, and to the right of the threshold)
the same goes for the visualizations where the threshold is moved to the left (-6: 30.

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The statement about smoke alarms is insane. There is a massive cost to false alarms: they are so common as to turn -smoke detectors- into what they really are, toast detectors. All you do, when you hear the alarm, is shut it off and go back to your routine, because you don't care that someone is making toast. That is, the false alarms almost guarantee that the sound of the toast detector will be ignored when there actually is a fire.
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-_. so-in votation we'd avoid the midrange 'indistinguishable-from-a-drunk vote' entropic lobe but here we're asking whether the high and low ends of voting are also some kind of 'indistinguishable-from-silliness vote' (cf polling members for their likelihood of voting for, and separately, voting against; A test of 'claimancy'. _-
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6: 20 Type II error should not be bounded by null distribution, and Type I should not be bounded by alternative distribution. This animation is misleading because it illustrates a fixed error sum with respect to cutoff. In reality, setting the cutoff at the intersection of the distributions -minimizes- this sum.
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To the sound guy: I like the new sound effects. FWIW, it reminds me of a failed game that I tried playing for a while called -Godus. -. It also seems to be taking some tonal cues from the Endless series (e. g.: Endless Space.
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I'm really glad this topic was given the room to breath over the last 3 episodes. Even in third year I come across people who have a complete misunderstanding of how p values work and what information they convey.
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The graphic is incorrect, type 1 error is the area under the null distribution to one side of the cutoff and the type 2 error is under the alternative distribution--neither is under both curves
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i get that it takes time to shoot these videos; but wouldn't it be better if the upload rates were faster than once a week, maybe once a day or 2 days
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7: 13
-When the alpha is 0. 05 that means that when the null is true, we'll correctly fail to reject [the null] 0. 95 or 95% of the time-

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Your course is amazing. Even though i took more than 3 statistics courses, i learn many things from you. Please keep up the great work!
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