Download All of Statistics: A Concise Course in Statistical Inference by Larry Wasserman PDF

By Larry Wasserman

WINNER OF THE 2005 DEGROOT PRIZE!

This e-book is for those who are looking to research likelihood and records speedy. It brings jointly the various major principles in sleek statistics in a single position. The publication is acceptable for college kids and researchers in information, laptop technological know-how, information mining and laptop learning.

This publication covers a wider diversity of themes than a standard introductory textual content on mathematical facts. It comprises glossy subject matters like nonparametric curve estimation, bootstrapping and category, themes which are frequently relegated to follow-up classes. The reader is thought to understand calculus and a bit linear algebra. No past wisdom of chance and information is needed. The textual content can be utilized on the complex undergraduate and graduate point.

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Read or Download All of Statistics: A Concise Course in Statistical Inference (Springer Texts in Statistics) PDF

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Extra resources for All of Statistics: A Concise Course in Statistical Inference (Springer Texts in Statistics)

Example text

J jx(x)= 21 211 ydy=-x(1-x) 21 2 4 f(x,y)dy=-x 4 X2 8 for -1 ::; x ::; 1 and fx(x) = 0 otherwise. 29 Definition. 7) and we write X II Y. Otherwise we say that X and Yare dependent and we write X IQ6OO' Y. 7) for all subsets A and B. Fortunately, we have the following result which we state for continuous random variables though it is true for discrete random variables too. 30 Theorem. Let X and Y have joint PDF fx,Y. Then X IT Y if and only if fx,Y(x, y) = fx(x)Jy(y) for all values x and y. 31 Example.

And Y rv Poisson(lL) and assume that X and Yare independent. j(>. + IL). 46 2. ) and Y rv Poisson(/L), and X and Yare independent, then X +Y rv Poisson(tt+>'). Hint 2: Note that {X = x, X + Y = n} = {X = x, Y = n - x}. 17. Y . x,y ) -_ { 0c(x + y2) o :::; x :::; 1 and 0 :::; y :::; otherwise. Find P (X 1 < ~ I Y = ~). 18. Let X rv N(3, 16). Solve the following using the Normal table and using a computer package. (a) Find JII'(X (b) Find JII'(X < 7). > -2). 05. < 4). 05. 19. 12). 20. Let X, Y rv Uniform(O, 1) be independent.

6. Let X have distribution F and density function f and let A be a subset of the real line. Let I A (x) be the indicator function for A: Let Y = IA(X), Find an expression for the cumulative distribution of Y. 14 Exercises 45 7. Let X and Y be independent and suppose that each has a Uniform(O, 1) distribution. Let Z = min{X, Y}. Find the density fz(z) for Z. Hint: It might be easier to first find J1D( Z > z). 8. Let X have 9. Let X rv CDF F. Find the CDF of X+ = max{O, X}. Exp(,6). Find F(x) and F-I(q).

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