Data collection, analysis, and interpretation.

Data collection, analysis, and interpretation:

Before you decide what to wear in the morning, you collect a variety of data: the season of the year, what the forecast says the weather is going to be like, which clothes are clean and which are dirty, and what you will be doing during the day. You then analyze that data. Perhaps you think, “It’s summer, so it’s usually warm.” That analysis helps you determine the best course of action, and you base your apparel decision on your interpretation of the information. You might choose a t-shirt and shorts on a summer day when you know you’ll be outside, but bring a sweater with you if you know you’ll be in an air-conditioned building.

Though this example may seem simplistic, it reflects the way scientists pursue data collection, analysis, and interpretation. Data (the plural form of the word datum) are scientific observations and measurements that, once analyzed and interpreted, can be developed into evidence to address a question. Data lie at the heart of all scientific investigations, and all scientists collect data in one form or another. The weather forecast that helped you decide what to wear, for example, was an interpretation made by a meteorologist who analyzed data collected by satellites
But collecting data is only one step in a scientific investigation, and scientific knowledge is much more than a simple compilation of data points. The world is full of observations that can be made, but not every observation constitutes a useful piece of data. For example, your meteorologist could record the outside air temperature every second of the day, but would that make the forecast any more accurate than recording it once an hour? Probably not. All scientists make choices about which data are most relevant to their research and what to do with that data: how to turn a collection of measurements into a useful dataset through processing and analysis, and how to interpret those analyzed data in the context of what they already know. The thoughtful and systematic collection, analysis, and interpretation of data allow it to be developed into evidence that supports scientific ideas, arguments, and hypotheses.