# Frequency Distribution Table: What is it used for?

### What is a Frequency Distribution Table?

Frequency tells you how often something occurs. The frequency of an observation in statistics tells you the number of times the observation occurs in the data. For example, in the following list of numbers, the frequency of the number 9 is 5 (because it occurs 5 times):

1, 2, 3, 4, 6, 9, 9, 8, 5, 1, 1, 9, 9, 0, 6, 9.

Tables can show either categorical variables (sometimes called qualitative variables) or quantitative variables (sometimes called numeric variables). You can think of categorical variables as being categories (like eye color or brand of dog food) and quantitative variables as being numbers.

Qualitative or quantitative? How to tell.

The following table shows what family planning methods were used by teens in Kweneng, West Botswana. The left column shows the categorical variable (Method) and the right column is the frequency — the number of teens using that particular method (image courtesy of KSU).

A frequency distribution table showing categorical variables.

Frequency distribution tables give you a snapshot of the data to allow you to find patterns. A quick look at the above frequency distribution table tells you the majority of teens don’t use any birth control at all.

### How to make a Frequency Distribution Table

Tally marks are often used to make a frequency distribution table. For example, let’s say you survey a number of households and find out how many pets they own. The results are 3,0,1,4,4,1,2,0,2,2,,0,2,0,1,3,1,2,1,1,3.

To make the frequency distribution table, first write the categories in one column (number of pets):

Next, tally the numbers in each category (from the results above):

Finally, count up the tally marks and write the frequency in the final column:

Another example of making a table:
How to draw a frequency distribution table.

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If you prefer an online interactive environment to learn R and statistics, this free R Tutorial by Datacamp is a great way to get started. If you're are somewhat comfortable with R and are interested in going deeper into Statistics, try this Statistics with R track.