Laboratory 3
Graphing Lab
Introduction
The purpose of this laboratory exercise is to gain experience in gathering and
displaying data from a simple experiment. When conducting an experiment, it is
important to define exactly what you are manipulating and what you are observing. The
general idea is to eliminate all factors that might influence the experiment and to make
very sure that what you are testing is exactly what you want to test. In this experiment
you are going to drop a ball and observe what happens.
You will make two measurements on each drop. The height from where you drop
the ball is the “dropped height”. This is the “independent variable” and will generally be
depicted on the graph as the x axis. The “bounce height” is the height that the ball
returns to after it bounces off the table. This is the “dependent variable” because this
height depends on the dropped height and it will be depicted on the y axis.
When graphing information to show a relationship between two variables, we do
not connect the data points. We only connect data point when we want to show a
change between data points. That is not the purpose of this exercise. Here we want to
see the general trend of the relationship. We draw a “line of best fit” or a “trend line” that
averages the data to show the general relationship. It also helps us minimize errors.
This line of best fit in this case will pass through the origin. (0,0). This point is valid in
this relationship because if I drop the ball from a height of zero, it will bounce zero.
Procedure
1. Position a Meterstick vertically on a flat surface, such as a wall or the side of a
lab table. Be sure the metric scale of the Meterstick is on the outside and secure
the Meterstick to the wall or lab table.
2. Drop a ball as close to the Meterstick as possible and measure (a) the height
dropped and (b) the resulting height bounced. Repeat this for three different
heights dropped and record all the data in Data Table 1.1. Make sure to identify
the independent and the dependent variables
3. Use graph paper to make a graph of the data in Data Table 1.1, being sure to
follow all the rules of graphing. Title the graph "Single Measurement Bounce
Height as a Function of Height Dropped."
4. After construction of the graph, but before continuing with this investigation,
answer the following questions
a. What decisions did you have to make about how you conducted the balldropping investigation?
b. Would you obtain the exact same results if you dropped the ball from the
same height several times? Explain.
c. Could you use your graph to predict a result for dropping the ball from
different heights? Explain why you could or could not?
5. Make ten more measurements for each of the three dropped heights used in
Data Table 1.1. Find the average height bounced for each level and record the
data and the averaged values in table 1.2.
6. Make a new graph of the averaged height bounced for each level that the ball
was dropped. Draw a best-fit line that includes the origin. Draw a straight line as
close as possible to as many data points as you can. This line should represent
the average trend of the data. Try to have about the same number of data points
on both sides of the line. Title this graph "Average Bounce height."
7. Select three heights that you have not used before. Use these new heights to
predict bounce heights from your two graphs. Compare how well both graphs
predict the heights that the ball will bounce for heights dropped that were not
tried previously. Record your predictions and the results in data table 1.3.
8. Repeat the experiment using a different size ball than in the first part. Record
your data in Data Tables 1.4, 1.5. Graph the results just as you did before and
use the graphs to predict results for dropped heights that were not used before.
Record your results in Data Table 1.6
9. What does the steepness of the (slope) of the lines tell you about the bounce of
the different Balls? Look at the slopes of your best fit lines and decide which ball
would be more fun and why?
Results
1. Describe the possible sources of error in the experiment.
2. Describe at least one way that the data concerning two variables is modified to
reduce errors in order to show general trends or patterns. (What did you do
differently between table 1.1 and 1.2?)
3. How is a graph modified to show the best approximation of theoretical, error-free
relationships between two variables? (What did you do to your graphs to show a
trend and minimize errors?)
4. Compare the usefulness of a graph showing exact data points connected dot to
dot and approximated straight line that has about the same number of data
points on both sides of the line.
5. Was the purpose of this lab accomplished? Why or why not? Please explain in
DETAIL.