Seven Common Graphs in Statistics
One goal of statistics is to present data in a meaningful way. It's one thing to see a list of data on a page, it's
another to understand the trends and details of the data. Many times data sets involve millions (if not billions) of
data values. This is far too many to print out in a journal article or sidebar of a magazine story. One effective
tool in the statistician's toolbox is to depict data by the use of a graph.
They say a picture is worth a thousand words. The same thing could be said about a graph. Good graphs convey
information quickly and easily to the user. Graphs highlight salient features of the data. They can show
relationships that are not obvious from studying a list of numbers. Graphs can also provide a convenient way to
compare different sets of data.
List of Common Graphs in Statistics
Different situations call for different types of graphs, and it helps to have a good knowledge of what graphs are
available. Many times the type of data determines what graph is appropriate to use. Qualitative data,
quantitative data and paired data each use different types of graphs.
Seven of the most common graphs in statistics are listed below:
1. Pareto Diagram or Bar Graph - A bar graph contains a bar for each category of a set of qualitative data.
The bars are arranged in order of frequency, so that more important categories are emphasized.
2. Pie Chart or Circle Graph - A pie chart displays qualitative data in the form of a pie. Each slice of pie
represents a different category.
3. Histogram - A histogram in another kind of graph that uses bars in its display. This type of graph is used
with quantitative data. Ranges of values, called classes, are listed at the bottom, and the classes with
greater frequencies have taller bars.
4. Stem and Left Plot - A stem and left plot breaks each value of a quantitative data set into two pieces, a
stem, typically for the highest place value, and a leaf for the other place values. It provides a way to list
all data values in a compact form.
5. Dot plot - A dot plot is a hybrid between a histogram and a stem and leaf plot. Each quantitative data
value becomes a dot or point that is placed above the appropriate class values.
6. Scatterplots - A scatterplot displays data that is paired by using a horizontal axis (the x axis), and a
vertical axis (they axis). The statistical tools of correlation and regression are then used to show trends
on the scatterplot.
7. Time-Series Graphs - A time-series graph displays data at different points in time, so it is another kind
of graph to be used for certain kinds of paired data. The horizontal axis shows the time and the vertical
axis is for the data values. These kinds of graphs can be used to show trends as time progresses.
What if none of the above graphs work for your data? Don't worry, although the above is a listing of some
of the most popular graphs, it is not exhaustive. There are more specialized graphs out there that may work