This title is part of the Pearson Modern Classics series. Pearson Modern Classics are acclaimed titles at a value price. Please visit www.pearsonhighered.com/math-classics-series for a complete list of titles. The revision of this well-respected text presents a balanced approach of the classical and Bayesian methods and now includes a chapter on simulation (including Markov chain Monte Carlo and the Bootstrap), coverage of residual analysis in linear models, and many examples using real data. Calculus is assumed as a prerequisite, and a familiarity with the concepts and elementary properties of vectors and matrices is a plus.
X2 OŹx n2 102 ° 1x ( a ) Prove that fx ( x ) = pfix ( 2 ) + ( 1 – p ) fax ( 2 ) . ( b ) Establish that px = puix + ( 1 – p ) Max where fix is the mean of X on IIį . ( c ) Establish that ož = poix + ( 1 - p ) oźx + p ( 1 – p ) ( 41x ...
This comprehensive study of probability considers the approaches of Pascal, Laplace, Poisson, and others. It also discusses Laws of Large Numbers, the theory of errors, and other relevant topics.
Presents a survey of the history and evolution of the branch of mathematics that focuses on probability and statistics, including useful applications and notable mathematicians in this area.
Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included – this is a modern method missing in many other books Probability and Statistics are studied by ...
This book is a fresh approach to a calculus based, first course in probability and statistics, using R throughout to give a central role to data and simulation.
Understanding Probability and Statistics: A Book of Problems
Probability and Statistics for Economists provides graduate and PhD students with an essential introduction to mathematical probability and statistical theory, which are the basis of the methods used in econometrics.
The book is also an excellent text for upper-undergraduate and graduate-level students majoring in probability and statistics.
A distinguishing character of the book is its thorough and succinct handling of the varied topics. This text is designed for a one-semester course on Probability and Statistics.
The book covers basic concepts such as random experiments, probability axioms, conditional probability, and counting methods, single and multiple random variables (discrete, continuous, and mixed), as well as moment-generating functions, ...