Descriptive Statistics for Summarising Data

Ray W. Cooksey
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Ray W. Cooksey: University of New England, UNE Business School

Chapter Chapter 5 in Illustrating Statistical Procedures: Finding Meaning in Quantitative Data, 2020, pp 61-139 from Springer

Abstract: Abstract This chapter discusses and illustrates descriptive statistics. The purpose of the procedures and fundamental concepts reviewed in this chapter is quite straightforward: to facilitate the description and summarisation of data. By ‘describe’ we generally mean either the use of some pictorial or graphical representation of the data (e.g. a histogram, box plot, radar plot, stem-and-leaf display, icon plot or line graph) or the computation of an index or number designed to summarise a specific characteristic of a variable or measurement (e.g., frequency counts, measures of central tendency, variability, standard scores). Along the way, we explore the fundamental concepts of probability and the normal distribution. We seldom interpret individual data points or observations primarily because it is too difficult for the human brain to extract or identify the essential nature, patterns, or trends evident in the data, particularly if the sample is large. Rather we utilise procedures and measures which provide a general depiction of how the data are behaving. These statistical procedures are designed to identify or display specific patterns or trends in the data. What remains after their application is simply for us to interpret and tell the story.

Keywords: Descriptive statistics; Graphs; Plots; Multivariate graphs; Frequencies; Central tendency; Variability; Standard scores; Exploratory data analysis; Probability; Normal distribution (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/978-981-15-2537-7_5

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