Today we’re going to begin our three-part unit on p-values. In this episode we’ll talk about Null Hypothesis Significance Testing (or NHST) which is a framework for comparing two sets of information. In NHST we assume that there is no difference between the two things we are observing and and use our p-value as a predetermined cutoff for if something seems sufficiently rare or not to allow us to reject that these two observations are the same. This p-value tells us if something is statistically significant, but as you’ll see that doesn’t necessarily mean the information is significant or meaningful to you.
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Reading for data science and machine learning
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statistically significant
It’s a crime that the intro doesn’t use “DFTBAQ” in the speech bubble for the intro.
I find it difficult to elevate my competence in statistics… maybe I am not simply predisposed to possess the proclivity of a Math Genius.
thanks this was extremely helpful
My god, I think after watching this about 3 times, I've got it
gold lame pants????
Why food examples? I am hungry now.hehe
Was that guy eating a clove of garlic?¿
6:10 golden words
we get assigned these videos for our stats class and I literally have no idea what ur talking about half the time lol
I'm in college now and have been watching videos from this channel since high school. Needless to say, they've been so helpful. So crazy and great I can find a resource as great as this on Youtube!
what
I miss John green
Unfortunately, the p value is responsible for the crisis in science. Statistical hypothesis tests don't know your hypothesis, and don't test anything! Only experiments can test. We must stop using p values as evidence, which they are not except under very specific circumstances, if we are to stop the rot inn science.
Delivery was much too fast and the graphics were not on the screen for long enough.
Could you please talk about effect size.
And if it’s as important as statistical significance. Especially with complete population stats (like census).
So we divided the us population into males and females, can we use effect size?
Echoing the comments about food…Food serves as a such a perfect source of relevant and manipulatable examples for a stats course. Three thoughts:
1) She does a great job using food in just this way in every one of the videos I've watched so far (up through 21)
2) People with eating disorders should look to Khan Academy for their video-based stats ejumukashun. Though inferior to CC in myriad ways and overall, at least his chicken scratch drawings and overly assumptive examples in no way resemble something comestible. His videos rival unadorned chicken breast in blandness and enjoyability. CC videos, well, chicken parm baked by a Neapolitano grandma named Maria!
3) She's an obvious plant by the Koch brothers and big-ag.
hungry while watching…and then 03:50 happens…………….
Notice how she says Buzzfeed 6:10
One 12min vid explained this topic better than six hours of classes.
4:54
I lost them when people started eating.
anyone else super grossed out by the men eating
THANK YOU!!
As someone who is studying statistics at uni, you explain these things better than most of my Professors. I feel like it fell into place now!
She could not have been more unclear in her definitions and examples. She literally made it as complex and confusing as possible even though this concept is actually not so.
Why the hell did the guy at 4.00 straight up bite into an onion????????????