In representing our data we move from reporting data to showing trends and patterns in the physical, chemical, and biological phenomena we observe. As we make decisions about the types of data we collect, we simultaneously need to think about how we will analyze and represent the data.

Data representations are driven by the types of data collected. Qualitative data describes your observations in words or pictures and quantitative data describes the experiment in terms of numbers. These data are often displayed in tables.

Graph data whenever possible. Relationships are more easily identified in a graphic presentation as compared to a table. Some data that cannot be graphed on coordinates can be expressed in pictorial form using other graphics such as a histogram. Supplement each graphic with a brief descriptive text following the general guidelines described above.

The title of your graph should be centered and placed just above the graph. Label both the x-axis and the y-axis. Be sure to indicate the units used in the experiment. Multiple data points should be graphed to provide a comparison among the experimental conditions.

To choose the type of graph that will best display your data, decide if your independent variable is continuous or discrete.Continuous variables are those measured on an ongoing scale such as length, temperature or time. The values range on a continuum, for example from 0 to 100 mm, or 0 to 100 °C, or 0 to 60 min. The intervals between numbers on a continuous scale are equal. That is, the distance from 1 to 3 mm is the same as from 13 to 16 mm.Categorical/ Discrete variables are described by separate categories. There is no continuum between the categories; there are no values between the categories. Examples of discrete variables include, dog breeds (greyhounds, pit bulls or terriers) or makes of car (BMW, Honda or Ford). In science, types of antibiotics are an example of categorical variables.

There are a few key elements to any graph…

DataRange

The graph is a graphical interpretation of some data. Generally, you will create a spreadsheet that generates some type of data, and use the graph to illustrate the data. When you define a graph, you will need some way to explain which data is being depicted. You can usually select the data you want with a range.

X and Y axes

As you may remember, the X axis is the stuff that goes along the horizontal border of the chart. The Y axis is the vertical stuff. Most spreadsheet programs try to guess which stuff you want plotted as the X axis and which you want as the Y axis. If the graph looks completely wrong, you might want to look for some kind of feature that allows you to change the X - Y orientation.

Upper and Lower Bounds

You might want to specify the upper and lower limits of the axes. The program will usually try to guess what you want, but you may still need to modify it.

Labels

There will usually be an option for setting or changing the labels on a graph. This will allow you to put informative (or misleading) labels on the graph to make it easier to read.

Graph type

You will usually get some type of option to change the type of graph that is displayed. See below for more information about graph types.

Common Mistakes

Mistake: Floating numbers: numbers that are not clearly attached to a line, making it difficult to assess whether the scaling and plotting are correct.

Solution: Stress the importance of labeling only the lines on the axis (if the data are numbers)

Mistake: Catchy titles that do not clearly indicate what the graph is representing.

Solution: Use both the dependent and independent variables in the title of the graph. Look at the axes labels, the data table or the experimental question.

Mistake: Units are left off of the axes' labels.

Solution: Learn to proofread and check for units of measurement.

Scoring Guide
When scoring your data table you will receive one point for each of the following:
Appropriate type of graph chosen to represent the data collected.
Appropriate title: A statement of the relationship between the dependent and independent variables of a statement of what is being tested.
Independent variable data is located on the horizontal axis of the graph.
Both horizontal and vertical axes are correctly labeled.
Axes labels include metric units if appropriate.
Numbered scale with correct intervals: consistent scaling, written on the lines, and with numbers that allow for the data to be plotted.
Data correctly plotted.

Misleading with Graphs

Graphs can send a very powerful message to people. The use of images makes a much more vivid impact that straight numbers. Graphs also have the capability to strengthen implications about data based on the type of graph, colors used, and other tools. Just because you see a graph does not mean you should believe it. Examine carefully where the data came from, and what it is telling you.

It is possible to make exactly the same data appear to have completely different meanings. Examine the figures below for an example:

If you look carefully, you will note that the graphs are both showing exactly the same thing, but by careful manipulation of the graph sizes, axis scales, and titles, the two charts appear to have exactly OPPOSITE meanings.

Web References for Graphs

XESS Corp.

Teacher’s PowerPoint for teaching graphing, scoring rubric, & common graphing mistakes