Describing Data Graphically and Numerically

The focus of this chapter is a discussion of methods for describing sets of data.

Topics Covered:

  • Basic concepts of a population and various types of sampling designs
  • Classification of the types of data
  • Organizing and summarizing qualitative and quantitative data
  • Describing qualitative and quantitative data graphically
  • Determining measures of centrality and measures of dispersion for a set of raw data
  • Determining measures of centrality and measures of dispersion for grouped data
  • Determining measures of relative position
  • Constructing a box whisker plot and its use in data analysis
  • Determining measures of association
  • Using statistical packages MINITAB, JMP, and Microsoft Excel

Learning Outcomes:

After studying this chapter, the reader will be able to

  • Select an appropriate sampling design for data collection.
  • Identify suitable variables in a problem and determine the level of measurement.
  • Organize, summarize, present and interpret the data.
  • Identify the difference between a parameter and a statistic.
  • Calculate measures of the data such as mean, mode, median, variance, standard deviation, coefficient of variation, and measure of association, and interpret them.
  • Identify outliers if they are present in the data.
  • Apply the statistical packages MINITAB, Microsoft Excel, and JMP to analyze the large body of data.

2.1 Getting Started with Statistics

2.1.1 What Is Statistics?

The term statistics is commonly used in two ways. On the one hand, ...

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