Descriptive Statistics

What Are Descriptive Statistics?

Descriptive statistics are the tools used to organize and summarize a collection of data so that its main features are easy to see. Rather than trying to predict or explain anything beyond the data at hand, they describe what the data shows. An investor who looks at a stock's average daily return over the past year, or at how much its monthly returns vary, is using descriptive statistics.

Common Measures

Descriptive statistics fall into a few broad groups. Measures of central tendency describe a typical value. The arithmetic mean is the average, found by adding all the values and dividing by the count. The median is the middle value when the data is sorted, and the mode is the value that appears most often. Measures of dispersion describe how spread out the values are. The range is the gap between the largest and smallest values, while the standard deviation measures how far values typically sit from the mean.

Why It Matters to Investors

Summary figures make it possible to compare assets quickly. Two funds might have similar average returns, yet one may have a much larger standard deviation, meaning its results swing more widely from period to period. The shape of the data also matters. A histogram shows how values are distributed, and skewness indicates whether returns lean toward large gains or large losses more often than a symmetric pattern would suggest.

Strengths and Limits

Descriptive statistics are simple to calculate and easy to communicate. However, they only describe the data in hand. They do not show whether past patterns will continue, nor do they prove that one thing causes another. Summary numbers can also hide important details, such as a few extreme values that pull the mean away from what most observations look like. For that reason, analysts often examine several measures together, along with a chart of the raw data.