do anyone know how to interpret correlation matrix?
451843
If you have correlation matrix A, then A(i,j) is the covariance between i and j, I think.  The matrix should be symmetric across its main diagonal.
917250
I'm going off memory here so be sure to check this.  I think the formula is the same, but the structure may be different.  Just trying to point you in the right direction.
396715
Took it last quarter, looked at it like a puzzle.  A puzzle is fun, math is not.  You start with the matrix given in the problem, and have to finish with ending matrix given.  Do what you need to do to get to the last matrix.  The best part, if you mess-up, just do another set.  There are no wrong answers, try doing it like a puzzle, more fun than Soduko.  Good Luck
784392
Here is what i found.  I'm not sure how right this is, but you can check it out.  Good Luck with your testing.
919222
The correlation coefficient is a number between -1 and 1 that measures the degree in which values in a sample space are linearly related. Graph the points and see how they are related spatially, if the points form something that looks like a blob  then the correlation coefficient is zero, or there is no linear relationship. If the points form a perfect line with a positive slope, then the correlation coefficient  is  1. If the points form a perfect line with a negative slope, then the correlation coefficient is  -1. So when you graph your sample space make a guess at where the data falls within the range of -1 to 1. Hope this helps.\n\nP.S. Use excel and you can graph those points quickly.
1116032
There is a possible package at the bottom of the link.  But, why not just use some of the Matlab functions written by others and do it yourself?  Should be straightforward.
929935
variations matter greatly in interpreting data.  Something might seem like it is returning significantly different results than the control but stat evaluation may show that the variations are minimal at best
1003267
You should look at the hamming distance between the two binary vectors, which is defined to be the number of coordinates that  have different values.  So in your example:\n  0001111000001100\n  0011110000001000\nhave 3 coordinates that have different values and\n  0011100000000000\n  0000000001111111\n10 coordinates that have different values. \n\nIf you define the correlation to be the number of coordinates in total minus the coordinates that have different values, you'll have a high correlation for the first pair, and a low correlation for the second pair.
1010952
Following site has very simplified way of explaining this. You might find it useful. \n\nPFC decoded ... http://www.dansdata.com/gz028.htm
872957
Look at them carefully, find out the diff between each number and it should be obvious.\n\nEquations?
100903
If A is an n-by-n symmetric positive definite matrix with real entries, that means ((v transpose)Av) > 0 for nonzero real n-by-1 column vectors v.\n\nConsider the 3x3 case with A equal to\n\n[ a b c ]\n[ b d e ]\n[ c e f ]\n\nLet u, v, and w be the nonzero column vectors\n\n[ 1 ]\n[ 0 ]\n[ 0 ]\n\n[ 0 ]\n[ 1 ]\n[ 0 ]\n\n[ 0 ]\n[ 0 ]\n[ 1 ]\n\nrespectively.  Then\n\n((u transpose)Au) = a > 0\n((v transpose)Av) = d > 0\n((w transpose)Aw) = f > 0\n\nCan you see how to generalize this for other values of n besides three and/or for matrices and vectors with complex entries?
846927
Sorry no one will be able to help you as we do not the data in #3.\n\nYou will need to figure this one out yourself...
808852
Sorry to say, you better pass on this data set.  \n\nNote that each row of numbers totals 100, as these are percentages, so the variables are correlated, and have limited application.\n\nI think your professor wants two of the variables to be somewhat independent, meaning one is not a function of the other.  Such as gas mileage and price, for example, if you had a list of automobile makes.\n\nRatio variables are those in which the ratio of two of the numbers have meaning, such as miles per gallon, for example.  If car A gets 15 mpg and car B gets 20 mpg, you can take the ratio of the two: 15/20 and compute 0.75, meaning car A gets 75% of the mileage of car B.
440750
Density Matrix.\n\ndiagonal part + nondiagonal part or\nstate probabilities + transition probabilities.
308472
Find yourself a z-statistic table and look up critical value in the table.  Check your stats book on how to interpret the table.\nhttp://www.math2.org/math/stat/distributions/z-dist.htm
830322
I just noticed that two rows are the same, right?  This is big, but I'll have to study up what it means.  Intuitively, I think that it means that the matrix has a null space, and thus and eigenvalue of zero.  \n\nor is it a type?\n\n\nRead up on it:\n\nhttp://en.wikipedia.org/wiki/Jordan_normal_form
248494
Ekta, it should be McNemar not McNerman.\n\nIt is the chisquare test for matched pairs. In a normal chisquare test you do the sum of  [(observed - expected)^2]/ expected and calculate the degrees of freedom. But in a matched chisquare analysis, the concordant pairs, that is a and d give no information, but only the discordant pairs are useful to us.\nHence, we have,\nChi square = (c-b)^2 / (b+c).\nThere is a continuity correction but I will not go into it. The degrees of freedom will again be 1.\n\nI hope you got what u meant to ask. If not, u can just comment further in this question and I will answer it.