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How matrix X1 X2 equals matrix X1 X2?
i think its pretty much the same thing because matrix X1 X2 IS ACTUALLY X1 X2
What is the vaule of x1?
X or if it says what "x" equals then plug that in and multiply
How do you use a variance-covariance matrix to obtain least squares estimates?
Suppose that you have simple two variable model: Y=b0+b1X1+e The least squares estimator for the slope coefficient, b1 can be obtained with b1=cov(X1,Y)/var(X1) the intercept term can be calculated from the means of X1 and Y b0=mean(Y)-b1*mean(X1) In a larger model, Y=b0+b1X1+b2X2+e the estimator for b1 can be found with b1=(cov(X1,Y)var(X2)-cov(X2,Y)cov(X1,X2))/(var(X1)var(X2)-cov(X1,X2)2) to find b2, simply swap the X1 and X2 terms in the above to get b2=(cov(X2,Y)var(X1)-cov(X1,Y)cov(X1,X2))/(var(X1)var(X2)-cov(X1,X2)2) Find the intercept with b0=mean(Y)-b1*mean(X1)-b2*mean(X2) Beyond two regressors, it just gets ugly.
What property is shown in 4 x1 equals 4?
The property that 1 is the identity for multiplication.
How do you find the mean of ordered pair?
Each element is the mean of the corresponding elements. Thus, the mean of (x1, y1) and ( x2, y2) is [( x1 + x2)/2, (y1 + y2)/2]
X plus one over x squared plus two?
it equals x1 it equals x1
Maxz equals 2x1 plus 2x2 stc 5x1 plus 3x2 equals 8 x1 plus 2x2 equals 4 x1 x2 equals 0 and integerssolve by ipp?
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How matrix X1 X2 equals matrix X1 X2?
i think its pretty much the same thing because matrix X1 X2 IS ACTUALLY X1 X2
Let A denote the event that the sum of 2 dice equals 11 Let x1 x2 denote the outcome first die equals x1 second die equals x2 Then?
A={(6,5),(5,6)} And The probability P(A) equals1/8
What is the vaule of x1?
X or if it says what "x" equals then plug that in and multiply
How do you write X equals -8 in its exponential form?
X1 = -81
What is the formula to calculate the slope?
It's m = y2 - y1/ x2- x1 It's m equals y2 minus y1 over x2 minus x1
What is the distance formula for college algebra?
d=the square root of everything that follows (x2-x1)2 + (Y2-Y1)2
How do you use a variance-covariance matrix to obtain least squares estimates?
Suppose that you have simple two variable model: Y=b0+b1X1+e The least squares estimator for the slope coefficient, b1 can be obtained with b1=cov(X1,Y)/var(X1) the intercept term can be calculated from the means of X1 and Y b0=mean(Y)-b1*mean(X1) In a larger model, Y=b0+b1X1+b2X2+e the estimator for b1 can be found with b1=(cov(X1,Y)var(X2)-cov(X2,Y)cov(X1,X2))/(var(X1)var(X2)-cov(X1,X2)2) to find b2, simply swap the X1 and X2 terms in the above to get b2=(cov(X2,Y)var(X1)-cov(X1,Y)cov(X1,X2))/(var(X1)var(X2)-cov(X1,X2)2) Find the intercept with b0=mean(Y)-b1*mean(X1)-b2*mean(X2) Beyond two regressors, it just gets ugly.
What property is shown in 4 x1 equals 4?
The property that 1 is the identity for multiplication.
X2 plus 8x-5 equals 0?
if you mean X²+8X-5=0: X1=-8/2 - Square root of ((8/2)²+5) X1=-4 - Square root of 21 X1 is about -8.58 X2=-8/2 + Square root of ((8/2)²+5) X2=-4 + Square root of 21 X2 is about 0.58
12 equals 3 x blank equals 6 x blank equals blank x 1 fill in the blanks?
12 equals 3x(4) equals 6x(2) equals (12)x1
