Introduction to Probability and Statistics expertly sheds light on the fundamental reasoning, methods and applications of statistics. From simple, clear explanations, students learn not only how to reason statistically, but also how to correctly interpret statistical results. The authors emphasize how to: Apply statistical procedures, uncover the meaning of statistical research in terms of their practical applications, evaluate the validity of assumptions behind statistical tests, determine what to do when those assumptions have been violated, and meaningfully describe real data sets.
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, ...
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 ...
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 ...
A bowl contains 12 red beads, 10 white beads, 25 blue beads, and three black beads. If one bead is drawn at random, what is the probability that it will be (a) blue; (b) red or white; (0) black; ((1) neither white nor black?
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
The book is also an excellent text for upper-undergraduate and graduate-level students majoring in probability and statistics.
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.
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;...
This is a textbook for an undergraduate course in probability and statistics.