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Numerical Summary Measures

In: Statistics for Business and Financial Economics

Author

Listed:
  • Cheng-Few Lee

    (Rutgers University Business School, Department of Finance and Economics)

  • John C. Lee

    (Center for PBBEF Research)

  • Alice C. Lee

Abstract

In this chapter, we extend the graphical descriptive method in data analysis by examining measures of central tendency, dispersion, position, and shape. All these numerical summary measures are important because they enable us to describe a set of data with only a small number of summary statistics. One use of these summary statistics is to compare individual observations from a data set. For example, a student in a statistics class could use one measure of central tendency, the class average, or mean, to determine how well her performance stacks up to the rest of the class. Measures of central tendency can also be used to compare two different sets of data. For example, a statistics teacher interested in comparing the performances of two different statistics classes could take the average, or mean, for each class and compare the two.

Suggested Citation

  • Cheng-Few Lee & John C. Lee & Alice C. Lee, 2013. "Numerical Summary Measures," Springer Books, in: Statistics for Business and Financial Economics, edition 3, chapter 0, pages 95-153, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4614-5897-5_4
    DOI: 10.1007/978-1-4614-5897-5_4
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