When you compute SEline and SEy, I notice you assume that y is dependent on x. Right? Isnt this a fallacy, assuming a dependence in one direction, a causality as opposed to a correlation?
My concern is that, apparently, we dont care about SEx - the squared error from the mean of x? Why is that?
With what degree of confidence/certainty can you interpolate a value/point? I mean to say, if I were to take a sample or a test, knowing what my x value will be, can I estimate with confidence where the y value might be?
@norwayte The 12% is unexplained. Real world examples are important here. Suppose x is height of a person and y is weight. Then 88% of the variation in weight can be explained by knowing someone's height. The other 12% is explained by either something else(diet, genetics, etc.), or just randomness (no real cause at all).
why is it 41/42?? someone explainnnnnn
johnchen0213 3 weeks ago
how do you do this automatically with excell?
4purs 3 weeks ago in playlist More videos from khanacademy
Take a drink every time he repeats himself!!!
Jaytaxman 1 year ago 3
SEline is just n*VAR(y). Correct?
CogitoErgoCogitoSum 1 year ago
When you compute SEline and SEy, I notice you assume that y is dependent on x. Right? Isnt this a fallacy, assuming a dependence in one direction, a causality as opposed to a correlation?
My concern is that, apparently, we dont care about SEx - the squared error from the mean of x? Why is that?
CogitoErgoCogitoSum 1 year ago
With what degree of confidence/certainty can you interpolate a value/point? I mean to say, if I were to take a sample or a test, knowing what my x value will be, can I estimate with confidence where the y value might be?
CogitoErgoCogitoSum 1 year ago
@CogitoErgoCogitoSum Can r or r^2 act as a "standard deviation" of sorts for making such inferences?
CogitoErgoCogitoSum 1 year ago
Someone told me about the area equation. They mentioned Pi R Squared. This is incorrect. Pi R Round. Cake R Squared. Get it right, people!
TreachMarkets 1 year ago
And the 12% is explained by what? Where come the 12% from?
norwayte 1 year ago
@norwayte The 12% is unexplained. Real world examples are important here. Suppose x is height of a person and y is weight. Then 88% of the variation in weight can be explained by knowing someone's height. The other 12% is explained by either something else(diet, genetics, etc.), or just randomness (no real cause at all).
BurkeyAcademy 1 year ago 2
This is perfect, but could you go back on the organic chemistry playlist? (I am a bit overloaded with numbers these days)
dalcde 1 year ago
@dalcde i miss math with numbers lol
PawntacticsCommando 1 year ago