Get All of Statistics: A Concise Course in Statistical Inference PDF

By Larry Wasserman

ISBN-10: 0387217363

ISBN-13: 9780387217369

ISBN-10: 1441923225

ISBN-13: 9781441923226

This e-book is for those that are looking to study chance and records fast. It brings jointly some of the major principles in sleek facts in a single position. The ebook is acceptable for college kids and researchers in statistics, computing device technological know-how, information mining and computing device learning.

This publication covers a much broader variety of subject matters than a regular introductory textual content on mathematical information. It comprises glossy issues like nonparametric curve estimation, bootstrapping and category, subject matters which are often relegated to follow-up classes. The reader is thought to understand calculus and a bit linear algebra. No past wisdom of likelihood and data is needed. The textual content can be utilized on the complex undergraduate and graduate level.

Larry Wasserman is Professor of records at Carnegie Mellon collage. he's additionally a member of the heart for computerized studying and Discovery within the college of machine technology. His study components comprise nonparametric inference, asymptotic conception, causality, and purposes to astrophysics, bioinformatics, and genetics. he's the 1999 winner of the Committee of Presidents of Statistical Societies Presidents' Award and the 2002 winner of the Centre de recherches mathematiques de Montreal–Statistical Society of Canada Prize in facts. he's affiliate Editor of The magazine of the yank Statistical Association and The Annals of Statistics. he's a fellow of the yank Statistical organization and of the Institute of Mathematical Statistics.

Show description

Read or Download All of Statistics: A Concise Course in Statistical Inference PDF

Best counting & numeration books

Download e-book for kindle: Lanczos algorithms for large symmetric eigenvalue by Ralph Wiloughby

First released in 1985, Lanczos Algorithms for giant Symmetric Eigenvalue Computations; Vol. I: idea provides history fabric, descriptions, and assisting concept on the subject of functional numerical algorithms for the answer of massive eigenvalue difficulties. This e-book offers with "symmetric" difficulties.

Automatic Differentiation: Applications, Theory, and - download pdf or read online

This assortment covers the cutting-edge in automated differentiation concept and perform. Practitioners and scholars will find out about advances in automated differentiation innovations and techniques for the implementation of strong and strong instruments. Computational scientists and engineers will enjoy the dialogue of functions, which offer perception into potent ideas for utilizing automated differentiation for layout optimization, sensitivity research, and uncertainty quantification.

Download e-book for kindle: Mathematikbuch zur Physik by Peter Hertel

Das Buch vermittelt die mathematischen Kenntnisse und Fertigkeiten, die für ein Studium der Physik und verwandter Gebiete unerlässlich sind. Es orientiert sich an einem Übersichtsbuch des Verfassers zur Theoretischen Physik und behandelt nur solche Gegenstände, die wirklich benötigt werden. Es ist ein schlankes und auf Verständnis, Übersicht und Anwendung angelegtes Buch, das sich leicht lesen lässt.

Download PDF by Arnoldo Frigessi, Peter Bühlmann, Ingrid Glad, Mette: Statistical Analysis for High-Dimensional Data: The Abel

This booklet gains learn contributions from The Abel Symposium on Statistical research for prime Dimensional info, held in Nyvågar, Lofoten, Norway, in may well 2014. the point of interest of the symposium used to be on statistical and laptop studying methodologies particularly constructed for inference in “big facts” occasions, with specific connection with genomic purposes.

Extra resources for All of Statistics: A Concise Course in Statistical Inference

Example text

Let F be the 1. JP'(X = CDF (1+x) = for x < 0 otherwise. fooo dx/(l +x) = J~oo du/u = log(oo) for a random variable X. Then: F(x) - F(x-) where F(x-) = limytx F(y); = 00 . 3 Some Important Discrete Random Variables 2. lP'(x x) = 1 - F(x); 4. If X is continuous then F(b) - F(a) lP'(a lP'(a It is also useful to define the inverse < < X < b) = lP'(a ::; X < b) X ::; b) = lP'(a ::; X::; b). CDF (or quantile function). 16 Definition. Let X be a random variable with CDF F.

The parameter p is usually unknown and must be estimated from data; that's what statistical inference is all about. In most statistical models, there are random variables and parameters: don't confuse them. THE GEOMETRIC DISTRIBUTION. X has a geometric distribution with parameter p E (0, 1), written X rv Geom (p), if J1D(X = k) = p(l - p)k-\ k:;:, 1. 4 Some Important Continuous Random Variables 27 We have that Think of X as the number of flips needed until the first head when flipping a coin. THE POISSON DISTRIBUTION.

Hence, Fx(x) = J~T Let Y = r(X) = logX. Then, Ay = {x: x:::; eY} and Fy(y) lP'(Y :::; y) = lP'(logX :::; y) lP'(X :::; eY) = Fx(e Y) = 1 - e-e". Therefore, fy(y) = eYe-e Y for y E R _ fx(s)ds = 42 2. 47 Example. Let X density of X is Uniform ( -1,3). Find the rv fx(x) = {1/4 o if - 1 ~ x < otherwlse. PDF of Y 3 Y can only take values in (0,9). Consider two cases: (i) 0 < y < 1 and (ii) 1 <::: y < 9. For case (i), Ay = [-JY, JYl and Fy(y) = fA fx(x)dx = (1/2)JY. For case (ii), Ay = [-1, JYl and Fy(y) = J~ y fx(x)dx = (1/4)(JY + 1).

Download PDF sample

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

by James

Rated 4.59 of 5 – based on 8 votes