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:

- 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.
- 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.
- 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.
- 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.
- 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.
- Scatterplots - A scatterplot displays data that is paired by using a horizontal axis (the
*x*axis), and a vertical axis (the*y*axis). The statistical tools of correlation and regression are then used to show trends on the scatterplot. - 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.

### Be Creative

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 for you.

You may also consider that sometimes situations call for graphs that haven't been invented yet. There once was a time when no one used bar graphs, because they didn't exist. Now bar graphs are programmed into Excel and other spreadsheet programs, and many companies rely heavily upon them. If you're confronted with data that you want to display, don't be afraid to use your imagination. Perhaps you'll think up a new way to help visualize data, and students of the future will get to do homework problems based on your graph.