1. Making and Interpreting Graphs
Graphing
Making and Interpreting Graphs

2. Why do we need graphs?
Patterns in the data can often be detected easier by using graphs
There are different types of graphs for varying types of data.
A graph is defined as a visual display of information or data.

3. Three types of Graphs 1) Line graphs 2) Bar graphs
3) Pie or Circle graphs

4. Line Graphs
Line Graphs are used to show the relationship of change between the independent variable and the dependent variable.
The independent variable is plotted on the x-axis (horizontal).
The dependent variable is plotted on the y-axis (vertical).

5. Line Graphs, cont’d.
It is possible to show more than one event on the same graph, as long as the relationship between the variables is the same.
When constructing a line graph, you must: 1) Make sure that your scale intervals are evenly spaced.
2) Be consistent with respect to units.

6. Bar Graphs
Bar graphs are useful for showing information collected by counting.
For example, if you took a survey of everyone’s favorite color, you could organize your results easily into a bar graph.
Independent variable= x-axis
Dependent variable= y-axis

7. Circle Graphs
Circle graphs are used to show how a fixed quantity is broken down into parts.
The circle represents the whole, and the individual parts are represented by percentages.

8. Rules for Graphing 1) Use at least 75% of the graph paper.
2) Label all axes. Have a title and key if necessary.
3) Always use graph paper when constructing a graph or use computer software.
4) Make sure that your tic marks are evenly spaced and consistent.

9. Spacing tic marks
To use most of the graph, there is an easy way to determine what your tic mark intervals should be.
Take the highest number you will graph on an axis and divide by the number of lines(squares) you have on your paper.
If the number is awkward, round up to the nearest workable interval.

10. Best Fit Line When graphing linear data, do not connect the dots!
You want to use a ruler to draw a straight line that best connects all the data points. This is called a line of best fit or linear regression.