Bayesian Methods for Statistical Analysis
by Borek Puza
Publisher: ANU Press 2015
Number of pages: 697
A book on statistical methods for analysing a wide variety of data. Topics: bayesian estimation, decision theory, prediction, hypothesis testing, hierarchical models, Markov chain Monte Carlo methods, finite population inference, biased sampling and nonignorable nonresponse. The book contains many exercises, all with worked solutions, including complete computer code.
Home page url
Download or read it online for free here:
by David M Diez, et al. - OpenIntro
Statistics is an applied field with a wide range of practical applications. This book is geared to the high school audience and is specifically tailored to be aligned with the AP Statistics curriculum. It is already being used by many high schools.
by Henry Lewis Rietz - Open Court Pub. Co
The book shifts the emphasis in the study of statistics in the direction of the consideration of the underlying theory involved in certain important methods of statistical analysis, and introduces mathematical statistics to a wider range of readers.
by Daniel McFadden - University of California, Berkeley
The contents: Economic Analysis and Econometrics; Analysis and Linear Algebra in a Nutshell; Probability Theory in a Nutshell; Limit Theorems in Statistics; Experiments, Sampling, and Statistical Decisions; Estimation; Hypothesis Testing.
by Ivan Lowe - scientificlanguage.com
Here I present statistics for the ordinary person. Examples are taken from ordinary life. The book begins with basic concepts behind the statistics and never gets harder than simple arithmetic. The course is presented as a series of key ideas.