
Absolute Frequency
Absolute frequency is a statistical term describing the number of times a particular piece of data or a particular value appears during a trial or set of trials. When the absolute frequency of values is tracked over the entire trial, the absolute frequency for a particular value can then be divided by the total number of values for that variable throughout the trial to get the relative frequency. Number of Alcoholic Drinks Per Week Number of Drinks per Week Example table showing the absolute frequency of responses There are a few observations you can make from the table displaying absolute frequency: more accountants drink some amount of alcohol than no alcohol. While absolute frequency is a very basic form of statistical analysis, it can be used as an input for more advanced statistical analysis, such as relative frequency. Absolute frequency is a statistical term describing the number of times a particular piece of data or a particular value appears during a trial or set of trials.

What Is Absolute Frequency?
Absolute frequency is a statistical term describing the number of times a particular piece of data or a particular value appears during a trial or set of trials. Essentially, absolute frequency is a simple count of the number of times a value is observed. Absolute frequency is usually expressed as a whole number and is considered a very basic level of statistical analysis.




Understanding Absolute Frequency
Absolute frequency is often a component of basic data collection. For example, if you ask 10 friends if blue is their favorite color and three say yes and seven say no, you have enough information to determine absolute frequency: the absolute frequency of "yes" is equal to three and that of "no" is equal to seven. The number of values tracked often increases with sample size or trial scope. For example, if you ask 100 people if their favorite color is blue, the absolute frequency will likely increase. However, there is no additional complexity in the tracking of how many times a given value occurs.
Absolute frequency is used in some data visualizations. For example, the absolute frequency of survey responses will often be displayed on a graph to provide an easily digested view of the majority of responses for a particular question.
Absolute frequency can be used to show the most commonly occurring data piece in a trial or study, but it isn't usually used as a primary statistical measurement.
Absolute Frequency vs. Relative Frequency
Absolute frequency can be the starting point for a more nuanced statistical analysis. Relative frequency, for example, is derived from absolute frequency. When the absolute frequency of values is tracked over the entire trial, the absolute frequency for a particular value can then be divided by the total number of values for that variable throughout the trial to get the relative frequency. The relative frequency is what we most often reference, whether it is the winning percentage of our favorite sports team or the percentage of fund managers that beat the market. Unlike absolute frequency, relative frequency is usually expressed as a percentage or fraction rather than a whole number.
Sometimes, when relative frequencies are very small, they are given in terms of "per thousand," "per million," etc., as in total number of crimes in a city per thousand people. Such adjustments are called "per capita."
Example of Absolute Frequency
Imagine an accounting conference that wants to collect data on drinking habits in the profession. The conference organizer asks a room of 50 accountants how many glasses of wine they have had over the past week. After each of the 50 accountants gives their answer, it is put into a table displaying the absolute frequencies.
Number of Alcoholic Drinks Per Week
Number of Drinks per Week
Example table showing the absolute frequency of responses
There are a few observations you can make from the table displaying absolute frequency: more accountants drink some amount of alcohol than no alcohol. However, the most valuable observations that can be made from this data set involve more analysis. For example, 50% of all the accountants at the conference have five or more drinks per week.
However, as a statistical study, this survey leaves much to be desired. For one, there is no demographic information beyond the profession of the respondents. The gender of the respondents is not revealed. This is important, given there are different health guidelines for alcohol consumption by sex. We also don't know the strength, or the alcohol by volume (ABV), of a particular drink being reported. Like absolute frequency, our example survey is just the beginning of a real analysis of alcohol consumption within the accounting profession.
Related terms:
Accounting
Accounting is the process of recording, summarizing, analyzing, and reporting financial transactions of a business to oversight agencies, regulators, and the IRS. read more
Adjusted Mean
The adjusted mean accounts for outlines and anomalies in a data set, thereby offering a more accurate mean average. read more
Bar Graph
A bar graph is a chart that plots data with rectangular columns representing the total amount of data for that category. read more
Chi-Square (χ2) Statistic
A chi-square (χ2) statistic is a test that measures how expectations compare to actual observed data (or model results). read more
Data Analytics
Data analytics is the science of analyzing raw data in order to make conclusions about that information. read more
Discrete Distribution
A discrete distribution is a statistical distribution that shows the probabilities of outcomes with finite values. read more
Poisson Distribution
A Poisson distribution is a statistical distribution showing the likely number of times that an event will occur within a specified period of time. read more
Population
Population may refer to the number of people living in a region or a pool from which a statistical sample is taken. See our population definition here. read more
Spurious Correlation
In statistics, a spurious correlation, or spuriousness, refers to a connection between two variables that appears causal but is not. read more
Statistics
Statistics is the collection, description, analysis, and inference of conclusions from quantitative data. read more