had a different slope, then it could be the angle that affects the erosion, not the farming
technique, for example. These are the controls. Finally, the dependent variable is the
amount of erosion because the farmer will measure the erosion to analyze its relatedness to
the farming technique.
Data and Experimental Error
Data can be collected in many different ways depending on what we are interested in finding
out. Scientists use electron microscopes to explore the universe of tiny objects and telescopes
to venture into the universe itself. Scientists routinely travel to the bottom of the ocean in
research submersibles to make observations and collect samples. Probes are used to make
observations in places that are too dangerous or too impractical for scientists to venture.
Probes have explored the Titanic as it lay on the bottom of the ocean and to other planets
in our solar system. Data from the probes travels through cables or through space to a
computer where it can be manipulated by scientists. Of course, many scientists work in a
laboratory and perform experiments and analyses on a bench top.
During an experiment, we may make many measurements. These measurements are our
observations that will be carefully recorded in an organized manner. This data is often
computerized and kept in a spreadsheet that can be in the form of charts or tables that
are clearly labeled, so that we won’t forget what each number represents. “Data” refers to
the list of measurements that we have collected. We may make written descriptions of our
observations but often, the most useful data is numerical. Even data that is difficult to
measure with a number is sometimes represented numerically. For example, we may make
observations about cleanliness on a scale from one to ten, where ten is very clean and one
is very dirty. Statistical analyses also allow us to make more effective use of the data by
allowing us to show relationships between different categories of data. Statistics can make
sense of the variability (spread) in a data set. By graphing data, we can visually understand
the relationships between data. Besides graphs, data can be displayed as charts or drawings
so that other people who are interested can see the relationships easily.
Asinjustabouteveryhumanendeavor, errorsareunavoidable. Inanexperiment, systematic
errors are inherent in the experimental setup so that the numbers are always skewed in one
direction or another. For example, a scale may always measure one-half ounce high. Like
many systematic errors, the scale can be recalibrated or the error can be easily corrected.
Random errors occur because no measurement can be made exactly precisely. For example,
a stopwatch may be stopped too soon or too late. This type of error is reduced if many
measurements are taken and then averaged. Sometimes a result is inconsistent with the
results from other samples. If enough tests have been done, the inconsistent data point can
be thrown out since likely a mistake was made in that experiment. The remaining results
can be averaged.
Not all data is quantified, however. Our written descriptions are qualitative data, data that