Types of Data

There are different types of data that can be collected in an experiment. Typically, we try to design experiments that collect objective, quantitative data.

Objective data is fact-based, measurable, and observable. This means that if two people made the same measurement with the same tool, they would get the same answer. The measurement is determined by the object that is being measured. The length of a worm measured with a ruler is an objective measurement. The observation that a chemical reaction in a test tube changed color is an objective measurement. Both of these are observable facts.

Subjective data is based on opinions, points of view, or emotional judgment. Subjective data might give two different answers when collected by two different people. The measurement is determined by the subject who is doing the measuring. Surveying people about which of two chemicals smells worse is a subjective measurement. Grading the quality of a presentation is a subjective measurement. Rating your relative happiness on a scale of 1-5 is a subjective measurement. All of these depend on the person who is making the observation – someone else might make these measurements differently.

Quantitative measurements gather numerical data. For example, measuring a worm as being 5cm in length is a quantitative measurement.

Qualitative measurements describe a quality, rather than a numerical value. Saying that one worm is longer than another worm is a qualitative measurement.

Quantitative Qualitative
Objective The chemical reaction has produced 5cm of bubbles. The chemical reaction has produced a lot of bubbles.
Subjective I give the amount of bubbles a score of 7 on a scale of 1-10. I think the bubbles are pretty.

 

Example Experiment

An experiment might be conducted to test the hypothesis that phosphate limits the growth of algae in freshwater ponds. A series of artificial ponds are filled with water and half of them are treated by adding phosphate each week, while the other half are treated by adding a salt that is known not to be used by algae. The independent variable here is the phosphate (or lack of phosphate). The experimental or treatment cases are the ponds with added phosphate and the control ponds are those with the salt that is known to not be used by algae. Just adding something is also a control against the possibility that adding extra matter to the pond has an effect. If the treated ponds show lesser growth of algae, then we have found support for our hypothesis. If they do not, then we reject our hypothesis. Be aware that rejecting one hypothesis does not determine whether or not the other hypotheses can be accepted; it simply eliminates one hypothesis that is not valid (Figure 1.4). Using the scientific method, the hypotheses that are inconsistent with experimental data are rejected.

How many times should you perform your test? How many samples should be in each test? The answer is “as many as is feasible”. For the purposes of educational laboratory experiences, that answer is typically around three times. However, if you were testing a new drug, you would need many more than three samples in order to show that the drug was safe and effective!

References

OpenStax, Biology. OpenStax CNX. May 27, 2016 http://cnx.org/contents/s8Hh0oOc@9.10:RD6ERYiU@5/The-Process-of-Science.

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Types of Data by Lisa Bartee is licensed under a Creative Commons Attribution 4.0 International License, except where otherwise noted.

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