Advertisement

Descriptive Statistics

  • Michael Havbro Faber
Part of the Topics in Safety, Risk, Reliability and Quality book series (TSRQ, volume 18)

Abstract

Decisions take basis in knowledge and information, which in engineering applications most often is available through different types of observations. To facilitate the process that observations can be collected and communicated consistently for the purpose of supporting decision making, it is of key importance to be able to describe and represent observations in standardized formats without distorting the information they contain. The present chapter, which comprises Lecture 3, provides an outline of the most common methods of what is referred to as descriptive statistics. First, various numerical summaries are provided including central measures, dispersion measures and measures of correlation. Thereafter, graphical representations are introduced including scatter diagrams, histograms, quantile plots, Tukey Box plots, quantile-quantile plots and Tukey mean difference plots. The different methods of descriptive statistics are illustrated throughout the chapter by means of data from experiments concerning the compression strength of concrete test specimens as well as road way traffic observations.

Keywords

Traffic Flow Sample Covariance Cumulative Frequency Scatter Diagram Sample Standard Deviation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 4.
    Benjamin, J.R., Cornell, C.A.: Probability, Statistics and Decision for Civil Engineers. McGraw-Hill, New York (1971) Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.Civil Engineering dept.DTU – Danish Technical UniversityKgs. LyngbyDenmark

Personalised recommendations