Proof of Cochran’s Theorem is given in the Wikipedia article.
Further suppose that $${\displaystyle r_{1}+\cdots +r_{k}=N}$$, where ri is the rank of $${\displaystyle B^{(i)}}$$. Idempotent matrices and Cochran’s theorem Theorem: If X = z ′ Q z where z = (z 1, …, z n) ′ and z 1, …, z n is a random sample from a normal distribution with mean 0 and variance 1 and Q is an idempotent matrix, then X … 5 0 obj ��J8
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In statistics, Cochran's theorem, devised by William G. Cochran, is a theorem used to justify results relating to the probability distributions of statistics that are used in the analysis of variance. Cochran's theorem Last updated November 29, 2019. In statistics, Cochran's theorem, devised by William G. Cochran, is a theorem used to justify results relating to the probability distributions of statistics that are used in the analysis of variance. Both these random variables are proportional to the true but unknown variance and the properties of the chi-squared distribution show that This fact is the foundation upon which many statistical tests rest. Rank additivity. 6 0 obj Quadratic Forms and Cochran’s Theorem • The conclusion of Cochran’s theorem is that, under the assumption of normality, the various quadratic forms are independent and χ distributed. �y#�^#�P���SR�. The following version is often seen when considering linear regression.Craig A. T. (1938) "On The Independence of Certain Estimates of Variances." 715
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The conclusion of Cochran’s theorem is that, under the assumption of normality, the various quadratic forms are independent and ˜2 distributed. Further suppose that. where r i is the rank of Q i.Cochran's theorem states that the Q i are independent, and each Q i has a chi-squared distribution with r i degrees of freedom. Statement. Less formally, it is the number of linear combinations included in the sum of squares defining Moreover, the characteristic function of the joint distribution of all the The third term is zero because it is equal to a constant times endobj (���l�|k?H�L�h�{�qV��\��F�ڝ������fSk�L+Xr��moeg�w����K_�W���ٛڕ�
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Q��*ɴ�A��fR�R�u]X����ʒD�$࠳9��Jp�;k�h$�=#�`�"�n��v�n� <> Cochran's theorem and its various extensions have been widely investigated in the literature since the theorem was first published in 1934; this is due, in part, to the importance of Cochran's theorem in the distribution theory for quadratic forms in normal random variables and in the analysis of variance. Rank … 13 0 obj endobj