One Sample Testing
In Measures of Variability, we describe the unitless measure of dispersion called the coefficient of variation. It turns out that s/x̄ is a biased estimator for the population coefficient of variation σ/μ. A nearly unbiased estimator is
where n is the sample size.
When the coefficient of variation is calculated from a sample drawn from a normal population, then the standard error can be calculated by
Using the unbiased sample coefficient of variation, we get
For normally distributed data, we can use the following test statistic
Example 1: Determine whether the population coefficient of variation for the data in range A4:A13 of Figure 1 (representing the length of certain biological organisms) is significantly different from 0. Also find the 95% confidence interval for the population coefficient of variation.
Figure 1 – Test of Coefficient of Variation
We see from the figure that p-value < alpha, and so the coefficient of variation is significantly different from zero. The 95% confidence interval is (.1079, .3403).
Two Sample Testing
For two samples you can test whether their populations have the same coefficient of variation (i.e. H0: σ1/μ1 = σ2/μ2) when the two samples are taken from normal distributions with positive means. The test statistic is
where V1 and V2 are the coefficients of variation for the two samples of size n1 and n2 and the pooled coefficient of variation is
The 1 – α confidence interval for the difference between the population coefficients of variation is
The test works best when the sample sizes are at least 10 and the population coefficients are at most .33.
Example 2: Determine whether there is a significant difference between the population coefficient of variation for weight and height based on the two independent samples in range of A3:B14 of Figure 2. Also find the 95% confidence interval for the difference between the population coefficients of variation.
Figure 2 – Two sample test for coefficient of variation
As you can see from Figure 2, there is no significant difference between the two coefficients of variation (p-value =.18) and the 95% confidence interval for the difference between the coefficients is (-.1614, .2306).