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

By Larry Wasserman

ISBN-10: 0387402721

ISBN-13: 9780387402727


This publication is for those that are looking to examine chance and records quick. It brings jointly a few of the major principles in glossy facts in a single position. The ebook is acceptable for college students and researchers in records, laptop technological know-how, information mining and computing device learning.

This booklet covers a much broader variety of issues than a customary introductory textual content on mathematical records. It contains smooth issues like nonparametric curve estimation, bootstrapping and type, issues which are often relegated to follow-up classes. The reader is believed to grasp calculus and a bit linear algebra. No prior wisdom of chance and information is needed. The textual content can be utilized on the complicated undergraduate and graduate point.

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

Example text

We get probabilities from a PDF by integrating. A PDF can be bigger than 1 (unlike a mass function). For example, if f(x) = 5 for x E [0,1/5] and 0 otherwise, then f(x) ~ 0 and f f(x)dx = 1 so this is a well-defined PDF even though f(x) = 5 in some places. In fact, a PDF can be unbounded. For example, if f(x) = (2/3)x- 1/ 3 for 0 < x < 1 and f(x) = 0 otherwise, then f f(x)dx = 1 even though f is not bounded. 14 Example. Let . 15 lemma. 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.

Show that Hint: First prove this for I = {I , ... ,n}. 5. Suppose we toss a fair coin until we get exactly two heads. Describe the sample space S. What is the probability that exactly k tosses are required? 6. Let n = {O, 1, ... ,} . e. , if IF'(A) = IF'(B) whenever IAI = IBI, then IF' cannot satisfy the axioms of probability). 7. Let Ab A 2, . be events. Show that Hint: Define Bn and that = An - U:-: Ai. Then show that the Bn are disjoint U:=l An = U:=l Bn. 8. Suppose that IF'(Ai) = 1 for each i.

What is the probability of another head? " Now suppose that the experiment was carried out as follows: We select a coin at random and toss it until a head is obtained. " 21. ) Suppose a coin has probability P of falling heads up. If we flip the coin many times, we would expect the proportion of heads to be near p. We will make this formal later. 3 and n = 1,000 and simulate n coin flips. Plot the proportion of heads as a function of n. 03. 22. ) Suppose we flip a coin n times and let P denote the probability of heads.

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All of Statistics: A Concise Course in Statistical Inference (Springer Texts in Statistics) by Larry Wasserman

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