A single measure has the ability to describe certain aspects of a data set. Here are a few measures that can be used to give an idea about different characteristics of a data set:
1. Mean: The mean is commonly known as the average. To calculate the mean of a data set, you sum up all the data points and then divide by the number of data points. This gives you a central value around which the data points are spread.
2. Median: The median is another measure of central tendency. To find the median of a data set, you sort the data points in increasing order and then select the middle value. If there are two middle values (in the case of an even number of data points), you take their average. The median is a good measure to use when your data set has outliers or is skewed, because it is not affected by these elements.
3. Mode: The mode is the value that appears most frequently in the data set. It gives you a common value for your data. In some cases, a data set can have more than one mode.
4. Range: The range provides a measure of spread for your data. It is calculated by subtracting the smallest value in the dataset from the largest value.
5. Standard Deviation: This is a measure of how spread out the numbers in the data are. The standard deviation is the square root of the variance.
6. Variance: This is another measure of spread. The variance is calculated by taking the average of the squared differences from the Mean.
7. Coefficient of Variation: This is a relative measure of variability in comparison to the mean.
It should be noted, however, that these single measures only describe one aspect of the data and may not give a comprehensive overview of the data set. Hence, using multiple measures together can provide a more informative summary of the data.