Beginning with the historical background of probability theory, this thoroughly revised text examines all important aspects of mathematical probability - including random variables, probability distributions, characteristic and generating functions, stochatic convergence, and limit theorems - and provides an introduction to various types of statist
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 ...
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, ...
Probabilities are numbers of the same nature as distances in geometry or masses in mechanics. ... After analyzing the distribution of the data via the methods of exploratory data analysis the next step is statistical inference, ...
Alternative Methods of Regression BISGAARD and KULAHCI : Time Series Analysis and Forecasting by Example BISWAS, DATTA, FINE, and SEGAL Statistical Advances in the Biomedical ...
This is caused by increasing significance of various uncertainties affecting performance of complex technological systems.
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.
The text includes many computer programs that illustrate the algorithms or the methods of computation for important problems. The book is a beautiful introduction to probability theory at the beginning level.
This is a textbook for an undergraduate course in probability and statistics.
What is statistics? Useful mathematical notation; Describing distributions of measurements; Probability; Random variables and probability distributions; The binomial probability distribution; The normal probability distribution; Statistical inference; Inference from small samples;...
The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo (MCMC). Additional