1. GRAPHING!

4. GRAPHING NOTES
1. LINE GRAPHS ARE GENERALLY USED
IN SCIENCE. THEY USUALLY SHOW
CHANGE OVER TIME. THEY
CAN SHOW TRENDS IN DATA.
*A TREND IS A PATTERN.

5. 2. YOU MUST USE A RULER WHEN
MAKING A GRAPH.

6. 3. BEGIN BY DRAWING YOUR X AND Y
AXIS. IF TIME IS A VARIBLE, TIME
SHOULD GO ON THE X AXIS.
*The independent variable should be on the
x-axis while the dependent variable is on the
y-axis.

7. 4. LABEL BOTH OF YOUR AXES (DON’T
FORGET THE UNITS)

8. 5. LOOK AT YOUR DATA. WHAT ARE THE HIGHEST AND LOWEST DATA
POINTS? USE THESE NUMBERS TO
DETERMINE THE SCALE ON EACH
AXIS.
*The numbers must go by equal increments.
Example : 2, 4, 6, 8, 10 or
15, 30, 45, 60, 75, 90 or
6000, 12000, 18000, 24000

9. 6. PLOT YOUR DATA POINTS ON YOUR
GRAPH.
-Use a line of BEST FIT for your data points.
Do NOT just connect the dots. We are
looking for patterns – a straight line or a
curve.

10. 7. TITLE YOUR GRAPH. THE TITLE
SHOULD BE YOUR INDEPENDENT
VARIABLE VS. YOUR DEPENDENT
VARIABLE.
Example – How does increasing the amount
of fertilizer affect the number of
flower blossoms?
IV =
Amount of fertilizer
DV =
Amount of flower blossoms
Title – Amount of fertilizer VS. the amount
of flowers that blossom.

11. 8. GRAPHS MUST BE NEAT AND
ACCURATE.

12. Graph Grading
Appropriate type of graph used
Descriptive Title
Both axes labeled and with units
Number scale uses equal increments.
Graph is neat and data is plotted accurately.

13. Notice best fit can be a curve.

14. This graph shows that the variables have a
Example 1:
the extension of a spring against the weight on it.
extension (cm)
weight (N)
This graph shows that the variables have a
direct correlation. As one increases it causes
the other to increase.

15. This graph shows that the variables have a
inverse correlation. As one increases it causes
the other to decrease.

16. This graph shows that the variables have a
NO correlation.