Stat 312 Course Notes, 140 pages done in LaTeX

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Interpretation of e[y|x] in the two treatment a &b . The spanning set of the columns of a matrix . 2. 7 changing matricies (for fun and pro t) . 2. 9. 4 computation of , y, h, and 2, in terms of the qr decomposition . 2. 9. 5 expectation, variance, and covariance in a linear regression model . Expectation, variance, and covariance with random variables . Expection, variance, and covariance with vectors and matricies . Important formulas for linear regression with hat matricies . 4. 3 distribution of a function of a random variable . 5. 4. 2 finding new power series from old ones . 5. 3. 2 applications: kth moment of a random variable x: e(cid:2)x k(cid:3) . Properties of riemann integrals on bounded variation functions . 6. 2. 2 review of common integrals of trig functions . Proof of weak law of large numbers by tchebyche inequality . 8 convergence of sequences and series of functions. Matrix algebra is essential for applications of probability in various elds:

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