What is a graph?
A graph is a representation of your data that shows the overall trend / "message" or your results.
A graph should show the information at a brief glance (trendline / best-fit curve) without too much close
examination. However, it should also contained the detailed information (specific data points).
It should be easy to read!
To this end a graph should be easily decipherable and should follow the general guidelines below. Note:
it is bad to have excess information.
Graphing Rubric (What you’re graded on)
1. Must be on graph paper, or through a graphing program (e.g. excel)
2. Must be neat
 do NOT hand draw extra lines if you run out of space
 plan ahead and redo it if necessary
3. Title
 Typical in chemistry: Y vs X
ex: catecholamine concentrations over time
 Preferable in Biology: conclusive statement of data,
ex: height increases jump distance
ex: differential catecholamine increases upon air exposure in green sturgeon
 Should NOT say "enzyme lab" or jump lab or jump data. This is the title of the lab from
the lab manual. The title of your graph should reflect the experiment.
4. X-axis independent value
5. Y-axis dependent value
6. Axis in scale
ex: 50,60,70,80
Things NOT to do: don't use uneven numbering: 1,2,4,5,9
Don’t use “unnatural” spacing: 3.5, 7, 10.5 etc.
Remember, this is meant to be easy to read
7. Spacing- your data should take up at least half of your graph space.
8. Axis labeled with dimension (height, distance, volume, concentration, etc) and unit (usually in
parentheses) of measurement
 Do not literally label your axis x & y
- x is simply a way of saying the horizontal axis
- y is simply a way of saying the vertical axis
 Axis does not necessarily begin at 0 (if data points range from 100-120, don't begin graph
at 0, start closer to 100, maybe 90)
- if your data doesn't have a 0, then DON'T include a 0 point
- Spread you data points out. A good rule of thumb is that your range of data points
should cover more area than your empty space.
 Preferable to have some space after the last data point (and before if not starting at 0,
although negative numbers are acceptable)
9. Data must be in S.I. (International Standard) Units / metric (or derivative thereof, ex: micrometer
instead of meter)
- weight (grams)
- volume (liters)
- distance (meters)
- temp (celsius)
- pressure (mmHg)
- absorbance (AU)
- concentration (Molarity) or (grams/liter)
10. Best fit “curve” / Trendline  The most difficult part of graphing. A curve is supposed to represent an average of your
data, it should reflect the pattern you believe the data supports.
 Things to keep in mind:
 when using categories on the x-axis (no trend), the graph should be represented
using a bar graph
 a line is a curve, just with zero curve. If you think the graph shows a line, use a
ruler. Curves should be hand drawn.
 Excel has algorithms that may draw trend lines. Be careful of using these, unless
you think the graph supports a straight line, they are unreliable.
 Curve does NOT have to hit first or last data point
 Extrapolate your curve both forward and back
 Extrapolation - Graphing is predictive, and should reflect that by extending your curve
both forward and back.
11. Legend (if multiple curves)
Note: Rules are sometimes meant to be broken. I will occasionally hand out extra points when reason
overcomes the rules above.
Significant figures are generally not counted, however they should be within reason. The rule is if you
measurement has significant figures to a particular decimal point, the result of your calculation should
go out to the same decimal point.
Ex: if your measured data is 10.3 cm then your calculated average should go out to the nearest .1 cm.
10.3 cm, 10.1 cm and 10.4cm would average out to be 10.3cm not 10.26666 cm.
In chemistry (and biology too), the calculation of significant figures needs to be more precise, however,
this course will not focus on making these calculations.