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Introduction to Statistics and Data Visualisation

  • Yuri A. W. Shardt

Abstract

This chapter introduces the reader to the fundamentals of descriptive statistics and data visualisation. Descriptive statistics focus on the development of methods for describing a given data set. They can be divided into two main groups: measures of central tendency, which examine the average behaviour of the data set, and measures of dispersion, which examine the spread of the data set. Measures of central tendency, such as the mean, mode, and median, are introduced, while measures of dispersion considered include the range, standard deviation, variance, median absolute difference, and skew. Also, quantiles and outliers are introduced as ways to describe a data set. Data visualisation focuses on developing a set of rules for effectively displaying data visually. Common data visualisation methods such as bar charts, histograms, pie charts, line charts, time series plots, box-and-whisker plots, scatter plots, probability plots, tables, and sparkplots are explained with detailed examples and methods of construction. The different approaches are illustrated with suitable examples, including a comprehensive analysis of a data set from a friction factor experiment. By the end of this chapter, the reader should be able to apply the principles of data description and visualisation to meaningfully portray the key properties of a given data set.

Keywords

Reynolds Number Scatter Plot Friction Factor Central Tendency Decimal Place 
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. Daniel C, Wood FS (1980) Fitting equations to data, 2nd edn. Wiley, New YorkGoogle Scholar
  2. Davies L, Gather U (1993) The identification of multiple outliers. J Am Stat Assoc 88(423):782–792CrossRefGoogle Scholar
  3. Gerhart PM, Gross RJ, Hochstein JI (1992) Fundamentals of fluid mechanics. Addison-Wesley Publication Co., ReadingGoogle Scholar
  4. Hyndman RJ, Fan Y (1996) Sample quantiles in statistical packages. Am Stat 50(4):361–365Google Scholar
  5. Lin B, Recke B, Knudsen JK, Jørgensen SB (2007) A systematic approach for soft sensor development. Comput Chem Eng 31:419–425CrossRefGoogle Scholar
  6. Tufte ER (1997) Visual and statistical thinking: displays of evidence for making decisions. Graphics Press LLC., CheshireGoogle Scholar
  7. Tufte ER (2001) The visual display of quantitative information. Graphics Press LLC., CheshireGoogle Scholar
  8. Varberg DE (1963) The development of modern statistics. The Mathematics Teacher 56(4):252–257Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Yuri A. W. Shardt
    • 1
  1. 1.Institute of Automation and Complex Systems (AKS)University of Duisburg-EssenDuisbergGermany

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