2018年5月23日 · $\begingroup$ do you mean the sign of the correlation coefficient is always the same the sign of any one the two regression coefficients ?@Jean-Claude Arbaut $\endgroup$ – Hussien Mohamed Commented May 22, 2018 at 22:47

Need help for an explanation for correlation coefficient. 2 Estimate the correlation coefficient of a two-dimentional normal distribution $(X,Y)$, given some samples of $(|X|, |Y|)$

I've been looking all over the internet and have been having trouble finding good uses of a covariance matrix to find the correlation coefficient. I know that, from a simple $2 \times2$ variance-covariance matrix, the correlation is given by $\mathrm{COR}\left(X,Y\right)=\frac{\mathrm{COV} \left(X,Y\right)}{\sqrt{Var\left(X\right)\cdot V …

2014年12月17日 · How to find the Correlation coefficient? I thought about making the formula $$\frac{1}{4}\text{ from intervals }0\leq x \leq 2, 0\leq y \leq 2$$ But it makes less and less sense as i move on since i don't even have all the values for the pmf. Any help?

2021年6月9日 · Correlation coefficient and regression line : Geometric intuition. 0. Linear regression correlation ...

Correlation coefficient of two continuous random variables. Ask Question Asked 7 years, 11 months ago.

2018年9月17日 · I've been looking all over the interwebs and have been having trouble finding good uses of a covariance matrix to find the correlation coefficient. For example, given a problem like: Suppose th...

2015年6月19日 · How then do I find the correlation coefficient? I have knowledge of only the definitions of elementary terms in the topic of regression, and I am self-studying this. I am sure the problem must have a very easy solution as it is meant to be solved in a few minutes with an extremely elementary knowledge of statistics.

Find the correlation coefficient for the random variables $X$ and $Y$ having joint density $f(x,y)=2$ for $0 < x \leq y<1$.

So if you have the s.d. for X, you just need to find $\sum_{k=1}^{n} x_{k}^{2} $ and you will have everything needed to calculate the estimate variance. Just manipulate the variance formula a little to get it: $\sum_{k=1}^{n} x_{k}^{2} = \sigma_{X}^{2} +n\bar{X}^{2}$