Collecting And Analyzing Data

Most experiments measure a variable—the dependent variable. This measurement provides quantitative data, data measured in numbers. For example, in the experiment above, scientists measured the distance of an owl's strike from the prey's head in centimeters, as shown in step 0 of Figure 1-9. An event's duration in milliseconds is also an example of quantitative data.

Biologists usually score the results of an experiment by using one of their senses. They might see or hear the results of an experiment. Scientists also extend their senses with a microscope for tiny objects or a microphone for soft sounds. In the owl experiment, biologists extended their vision with infrared cameras.

Analyzing and Comparing Data

After collecting data from a field study or an experiment and then organizing it, biologists then analyze the data. In analyzing data, the goal is to determine whether the data are reliable, and whether they support or fail to support the predictions of the hypothesis. To do so, scientists may use statistics to help determine relationships between the variables involved.

They can then compare their data with other data that were obtained in other similar studies. It is also important at this time to determine possible sources of error in the experiment just performed. Scientists usually display their data in tables or graphs when analyzing it. For the owl study, biologists could have made a bar graph such as the one in Figure 1-10, which shows the average distance from the owl's strike relative to the mouse's head or the leaf in the light and in the dark.

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