Coefficient of Variation

To help you get the most out of IBM SPSS Statistics, the Version 1 SPSS experts want to highlight a new feature introduced in Version 31: the Coefficient of Variation (CV). This statistic is now available as a tick box in both the Frequencies and Descriptive Statistics procedures.

In IBM SPSS Statistics, you can work within a single, integrated interface to perform a wide range of statistical and analytical tasks. Whether you’re running descriptive statistics, regression models, advanced statistical procedures, or machine learning algorithms, SPSS provides a unified environment that supports both novice users and experienced analysts. It enables you to create publication-ready charts, tables, and decision trees—all within one tool. With its intuitive design, SPSS Statistics is easy to use, supports automation of analyses, integrates with open-source tools like R and Python, and offers built-in guidance to help you at every step.

To use it:

• In Frequencies: Go to Analyze > Descriptive Statistics > Frequencies, select your variables, then click the Statistics button. Tick Coefficient of Variation and run the procedure.
• In Descriptives: Go to Analyze > Descriptive Statistics > Descriptives, select your variables, then click the Options button. Tick Coefficient of Variation and proceed.

The Coefficient of Variation is a valuable addition to the suite of descriptive statistics available in SPSS. It complements other key measures such as mean, standard deviation, skewness, and kurtosis by offering a scale-independent way to assess variability. This makes it especially useful when comparing the relative dispersion of variables measured in different units or across different populations.

Whether you’re evaluating consistency in manufacturing processes, comparing investment risk, or analysing survey data, the Coefficient of Variation provides a clear, interpretable metric for relative variability. By integrating this option directly into the Frequencies and Descriptives procedures, Version 31 makes it easier than ever to include this insight in your standard statistical analysis output alongside other essential summaries that help describe and understand your data.