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# Probability

• ### Song: Divvy up the Stakes

A song about the Problem of Points, whose discussion in the 17th century led to the foundations of probability theory and expected value.  The lyric was written in 2017 by Lawrence M Lesser from The University of Texas at El Paso and may be sung tot he tune of the Sting #1 1983 Grammy-winning hit “Every Breath You Take”.

• ### Probabilistic Risk Assessment Procedures Guide for NASA Managers and Practitioners

Probabilistic Risk Assessment (PRA) is a comprehensive, structured, and logical analysis method aimed at identifying and assessing risks in complex technological systems for the purpose of cost-effectively improving their safety and performance. NASA’s objective is to better understand and effectively manage risk, and thus more effectively ensure mission and programmatic success, and to achieve and maintain high safety standards at NASA. This PRA Procedures Guide, in the present second edition, is neither a textbook nor an exhaustive sourcebook of PRA methods and techniques. It provides a set of recommended procedures, based on the experience of the authors, that are applicable to different levels and types of PRA that are performed for aerospace applications.

• ### Bayesian Inference for NASA Probabilistic Risk and Reliability Analysis

This NASA-HANDBOOK is published by the National Aeronautics and Space Administration (NASA) to provide a Bayesian foundation for framing probabilistic problems and performing inference on these problems. It is aimed at scientists and engineers and provides an analytical structure for combining data and information from various sources to generate estimates of the parameters of uncertainty distributions used in risk and reliability models. The overall approach taken in this document is to give both a broad perspective on data analysis issues and a narrow focus on the methods required to implement a comprehensive database repository.

• ### Statistics: Basic Concepts for Astronomers

This presentation was given by Aneta Siemiginowska at the 4th International X-ray Astronomy School (2005), held at the Harvard-Smithsonian Center for Astrophysics in Cambridge, MA.

• ### Probability and Statistics in Aerospace Engineering

This resource was prepared to give the practicing engineer a clear understanding of probability and statistics with special consideration to problems frequently encountered in aerospace engineering. It is conceived to be both a desktop reference and a refresher for aerospace engineers in government and industry. It could also be used as a supplement to standard texts for in-house training courses on the subject.

• ### Introduction to Statistics (NASA Lesson)

These pages explain the following basic statistics concepts: mean, median, mode, variance, standard deviation and correlation coefficient (with example from the Institute on Climate and Planets).

• ### Collection: Calculators

Our online calculators and converters can help you in many daily tasks that require calculations to complete.

• ### Collection: Statistical Calculators

Free statistical calculators online.  Our basic statistical calculators will help you in common tasks you might encounter and deal mostly with simple distributions.

• ### The Integrated Medical Model (NASA Activity)

The Integrated Medical Model (IMM) is a Monte Carlo simulation-based tool designed to quantify the probability of the medical risks and potential consequences that astronauts could experience during a mission. In this activity, students will use Monte Carlo methods with a TI-Nspire™ to simulate and predict probabilities of CO2 headaches aboard the ISS.

NASA's Math and Science @ Work project provides challenging supplemental problems for students in advanced science, technology, engineering and mathematics, or STEM classes including Physics, Calculus, Biology, Chemistry and Statistics, along with problems for advanced courses in U.S. History and Human Geography.

• ### Models for Matched Pairs

This presentation is a part of a series of lessons on the Analysis of Categorical Data.  This lecture overs the following:  odds ratio, dependent proportion, marginal homogeneity, McNemar's Test, marginal homogeneity for greater than 2 levels, measures of agreement, and the kappa coefficient (weighted vs. unweighted).