Statistical Distributions,risk

Monte Carlo statistical methods, particularly those based on Markov chains, are now an essential component of the standard set of techniques used by statisticians. This new edition has been revised towards a coherent and flowing coverage of these simulation techniques, with incorporation of the most recent developments in the field. In particular, the introductory coverage of random variable generation has been totally revised, with many concepts being unified through a fundamental theorem of simulation.

Understand the application of VARIANCE, COUNTIFS, CORRELATION, MAXIFS, MINIFS, AVERAGEIFS, MEDIAN, MODE, RANK, QUARTILE

Leverage Minitab and Excel to master predictive modeling, statistical analysis, and data-driven insights.

Authors: Berry, Kenneth J., Mielke, Jr., Paul W., Johnston, Janis E.
Presents a methodological umbrella under which (1) disparate statistical methods are synthesized and integrated and (2) a number of new permutation statistical methods are developed
Synthesizes and integrates a large number of existing classical statistics under a common mathematical function
Provides computing algorithms for calculating permutation tests, and details the history of permutation statistical methods