Chapter 15. Statistical Techniques

Introduction

This chapter covers several topics that relate to basic statistical techniques. For the most part, these recipes build on those described in earlier chapters, such as the summary techniques discussed in Chapter 8, and join techniques from Chapter 14. The examples here thus show additional ways to apply the material from those chapters. Broadly speaking, the topics discussed in this chapter include:

  • Techniques for characterizing a dataset, such as calculating descriptive statistics, generating frequency distributions, counting missing values, and calculating least-squares regressions or correlation coefficients

  • Randomization methods, such as how to generate random numbers and apply them to randomizing a set of rows or to selecting individual items randomly from the rows

  • Techniques for calculating successive-observation differences, cumulative sums, and running averages.

  • Methods for producing rank assignments and generating team standings

Statistics covers such a large and diverse array of topics that this chapter necessarily only scratches the surface and simply illustrates a few of the potential areas in which MySQL may be applied to statistical analysis. Note that some statistical measures can be defined in different ways (for example, do you calculate standard deviation based on n degrees of freedom, or n–1?). If the definition I use for a given term doesn’t match the one you prefer, adapt the queries or algorithms shown here appropriately. ...

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