Final answer:
Variability refers to the degree to which data points in a dataset differ from each other. It is a measure of how spread out or dispersed the data is. The most common measure to calculate variability is the standard deviation.
Step-by-step explanation:
Alternative definition of variability:
Variability refers to the degree to which data points in a dataset differ from each other. It is a measure of how spread out or dispersed the data is. Variability quantifies the amount of diversity or variation present in a set of data.
How to calculate variability:
There are several ways to calculate variability, but the most common measure is the standard deviation (SD). The formula for calculating the sample standard deviation is as follows:
Step 1: Calculate the mean (average) of the data.
Step 2: Subtract the mean from each data point, and square the result.
Step 3: Calculate the sum of all the squared differences from step 2.
Step 4: Divide the sum obtained in step 3 by the number of data points minus 1 (for a sample) or by the number of data points (for a population).
Step 5: Take the square root of the result from step 4 to find the standard deviation.
Other measures of variability include the range, which is the difference between the highest and lowest values in a dataset, and the interquartile range (IQR), which is the difference between the first quartile (Q1) and third quartile (Q3) in a dataset. These measures give additional information about the spread of data.