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Covariance is a measure of how much two variables change together.
If one variable changes how much will the other change?
Example people's length and weight change together (within certain limits) taller people are in general heavier than shorter people. These two variables have great covariance.
Whereas eye color has little relationship to height. those two variables have small (or no) covariance.
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What is the meaning of analysis of covariance?
A mix of linear regression and analysis of variance. analysis of covariance is responsible for intergroup variance when analysis of variance is performed.
How do you calculate sample covariance?
See related link.
What is the difference between correlation and covariance?
Correlation is scaled to be between -1 and +1 depending on whether there is positive or negative correlation, and is dimensionless. The covariance however, ranges from zero, in the case of two independent variables, to Var(X), in the case where the two sets of data are equal. The units of COV(X,Y) are the units of X times the units of Y. correlation is the expected value of two random variables (E[XY]),whereas covariance is expected value of variations of two random variable from their expected values,
How 2 calculate a variance-covariance matrix?
See related link. You can use Excel, if you dataset is not too big. Generally, if I have a table of data, with n columns corresponding to n variables with N observations, I can calculate the covariance of columns a and b, using excel covar function, covar(range of first data values, range of second data values) To keep things organized, you may want to name the ranges of your columns and use them as the arguments in the covar.
Calculate the standard deviation of the portfolio with two securites first A proporiton 0.39 variance 160 second B proportion 61 and variance is 340 covariance of both is 190?
[((.39)^2)*160 +((.61)^2)*340+2*.61*.39*190]^.5 = 15.5323
