Lectures on Statistics
by Robert B. Ash
Publisher: University of Illinois 2007
These notes are based on a course that the author gave at UIUC in 1996 and again in 1997. No prior knowledge of statistics is assumed. A standard first course in probability is a prerequisite, but the first 8 lectures review results from basic probability that are important in statistics. Some exposure to matrix algebra is needed to cope with the multivariate normal distribution in Lecture 21, and there is a linear algebra review in Lecture 19.
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by Michael Lavine
Upper undergraduate or graduate book in statistical thinking for students with a background in calculus and the ability to think abstractly. The focus is on ideas and concepts, as opposed to technical details of how to put those ideas into practice.
by Wolfgang K. Hardle, Leopold Simar - Springer
The authors present multivariate data analysis in a way that is understandable to non-mathematicians and practitioners confronted by statistical data analysis. The book has a friendly yet rigorous style. Mathematical results are clearly stated.
by Brian S Blais - Save The Broccoli Publishing
This is a new approach to an introductory statistical inference textbook, motivated by probability theory as logic. It is targeted to the typical Statistics 101 college student, and covers the topics typically covered in the first semester.
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This book describes computationally-intensive statistical methods in a unified presentation, emphasizing techniques that arise in a wide range of methods. The book assumes an intermediate background in mathematics, computing, and statistics.