Since sample a has data more tightly clustered about the mean compared to sample b, we can say that the variance for sample a is lower than that for sample b.
What is variance:
Variability gets used to measure the central tendency's closeness to the values. A measure of central tendency that can get used is mean. Mean refers to the average for some given values and gets determined by dividing the sum of those values by the number of values. The variance refers to the average squared difference of each value from the mean.
When the variance is lower, the data is less spread out. Thus, data being more tightly clustered about the mean reflects lower variance. Since sample a has data more tightly clustered about the mean compared to sample b, it can be concluded that the variance for sample a is lower than that for sample b.
Learn more about variance here:
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