Probability, Statistics and Other Frightening Stuff

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advanced outlier identification techniques
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Beta Distribution
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CDF
Chauvenet's Criterion
Chi Squared Distribution
Continuous Unimodal Distributions
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cost engineering methods
data normality assessment
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estimating and forecasting
Excel statistical functions
Excess Kurtosis
General Beta Distribution
JB Statistic
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nonparametric analysis
Normal Copula
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parametric tests
Pareto Distribution
Pareto Minimum
Pearson's Linear Correlation
Peirce's Criterion
Potential Outlier
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Skewness Coefficient
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Spearman's Rank Correlation
statistical inference
Student's t-Distribution
Suspect Point
Triangular Distribution
Volume Iii
Weibull Distribution

Product details

  • ISBN 9781138065031
  • Weight: 880g
  • Dimensions: 156 x 234mm
  • Publication Date: 10 Sep 2018
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
  • Language: English
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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.

Alan R. Jones is Principal Consultant at Estimata Limited, an estimating consultancy service. He is a Certified Cost Estimator/Analyst (US) and Certified Cost Engineer (CCE) (UK). Prior to setting up his own business, he has enjoyed a 40-year career in the UK aerospace and defence industry as an estimator, culminating in the role of Chief Estimator at BAE Systems. Alan is a Fellow of the Association of Cost Engineers and a Member of the International Cost Estimating and Analysis Association. Historically (some four decades ago), Alan was a graduate in Mathematics from Imperial College of Science and Technology in London, and was an MBA Prize-winner at the Henley Management College (. . . that was slightly more recent, being only two decades ago). Oh, how time flies when you are enjoying yourself.

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