A graph is a diagram that is meant to represent
data
and to portray a relationship. Analyzing graphs is useful for
determining the general trend, relating the results of an experiment to
the hypothesis and for formulating hypotheses for future experiments.
When analyzing graphs, it is important to determine what the graph is
displaying and why such information is pertinent to the experiment or to
the context of the question. More than one type of graph can be used to
represent a single set of data.
1
Distinguish between the various types of graphs. The main
types of graphs are picture graphs, bar graphs, line graphs and scatter
plots. A picture graph uses pictures to represent values. Bar graphs use
either vertical or horizontal bars to represent the values. Line graphs
use lines to represent the values. Scatter plots represent the data
with points, and then a best-fit line is drawn through some of the
points.
2
Read the title and axes of the graphs in order to determine
which type of data is being represented. The x-axis is the independent
variable, or that which can be changed. The y-axis is the dependent
variable, or that which depends on the independent variable. For
example, on a graph of the height of rose plants during a period of six
weeks, the x-axis would have the weeks, whereas the y-axis would have
the height.
3
Determine the general trend of the graph. In a picture
graph, look for the line with the highest amount of pictures. For a bar
graph, look for the highest bar. For a line graph and a scatter plot,
look at the slope of the line. If the line is pointing to the upper
right corner, then the slope is positive. If the line is pointing to the
lower right corner, then the slope is negative.
4
Look for data points that do not seem to fit the general
trend. Not all sets of data display a perfect trend. Examine such
points, and record them. If there is one bar, dot or part of the line
that is out of place, then this may not be significant enough to affect
the entire conclusion.
5
Use the graph to make predictions about future sets of data.
For example, if for each of the six weeks the plants increase in height
by 2 cm, then you would continue this trend in the prediction. If the
plant is 12 cm at week six, then a prediction at week seven would be 14
cm.
http://www.ehow.com/how_8482849_analyze-graphs.html
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