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Calculating R-Squared to see how well a regression line fits data
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why is line and variation in x interchangeable?
Sal be hittin those excel shortcuts 😉
Here's the question: IS THE ANSWER E?)
Which of the following tells us how strong the relationship is between two variables?
a) the slope of a line
b) the intercept of a line
c) the coefficient of determination
d) the coefficient of correlation
e) both C and D are correct
At 7:06 why does the SE line does not explain the error SE of difference from the mean of y
Why is the SE error by the line does not describe the error in mean of Y
i thought I was going insane learning the conditional probability, but this saved my day. More concrete and logical.
Amazing job, thanks a lot
YOU.ARE.GOD!
I LOVE YOU KHAN
for a one predictor model should i use R^2 or adjusted R^2
i am drujnkha
First year in statistics….do I use parentheses when doing the coefficient of determination? For example, I am confused now because I read that you can't have a negative correlation of determination. For instance, say you had Rxy = -.7….now, would that be like this (-.7)squared, or just -.7 squared…each gives different results….a negative and a positive…but I don't know which one to use? Thanks!
This helps a lot. Thank you very much. I hope I can do the same job if I have enough ability. I will be good if I can get a PhD degree in Engineering.
what about when the difference between the "best fit" line is much much larger than the mean and the squared error with the line of "best fit" is actually much larger than the squared error with the mean? then you get a negative r squared?
why is it 41/42?? someone explainnnnnn
Take a drink every time he repeats himself!!!
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!
@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).
And the 12% is explained by what? Where come the 12% from?