Probability, Statistics and Other Frightening Stuff (Volume II of the Working Guides to Estimating & Forecasting series) considers many of the commonly used Descriptive Statistics in the world of estimating and forecasting. It considers values that are representative of the ‘middle ground’ (Measures of Central Tendency), and the degree of data scatter (Measures of Dispersion and Shape) around the ‘middle ground’ values. A number of Probability Distributions and where they might be used are discussed, along with some fascinating and useful ‘rules of thumb’ or short-cut properties that estimators and forecasters can exploit in plying their trade. With the help of a ‘Correlation Chicken’, the concept of partial correlation is explained, including how the estimator or forecaster can exploit this in reflecting varying levels of independence and imperfect dependence between an output or predicted value (such as cost) and an input or predictor variable such as size. Under the guise of ‘Tails of the unexpected’ the book concludes with two chapters devoted to Hypothesis Testing (or knowing when to accept or reject the validity of an assumed estimating relationship), and a number of statistically-based tests to help the estimator to decide whether to include or exclude a data point as an ‘outlier’, one that appears not to be representative of that which the estimator is tasked to produce. This is a valuable resource for estimators, engineers, accountants, project risk specialists as well as students of cost engineering.

Probability Theory for Statistical Methods is a classic textbook on probability theory. It covers basic probability, random variables, and probability distributions, and serves as an essential resource for anyone studying statistics or related fields. A must-read for anyone interested in the mathematics of chance. This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work is in the "public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.

Probability and statistics are the parts of mathematics that deal with the rules that govern random events. They also collect, analyze, interpret, and display numerical data. The study of gambling and insurance in the 17th century gave rise to probability, which is now an essential tool in both the social and natural sciences. Measurements might be said to have its starting point in registration counts required millennia prior; however, as a distinct scientific field, it was developed in the early 19th century as a mathematical tool for analyzing such numbers and as the study of populations, economies, and moral actions. See probability theory and statistics for more in-depth, technical information on these topics.