Scientists Say: Uncertainty
Uncertainty (noun, “Un-SIR-ten-tee”)
In daily life, a person may be certain about some things but uncertain about others. For example, they may be certain they’ll eat breakfast one morning but uncertain if it will rain. In science, though, everything is uncertain. And scientists often measure that uncertainty.
Uncertainty is how much a measurement varies around an already-measured value. No measurement can be completely accurate. There will always be some error. Or there can be natural variation in whatever is being measured. So scientists will try to measure how much uncertainty can be found in their data. To represent that uncertainty, they place error bars around a point or line on a graph or chart. The bars’ size represents how much new measurements might be expected to vary around the value the scientists have found.
Sometimes scientists express uncertainty with the standard error of the mean. These bars represent where all potential measurements might fall, based on a random sample. Another way to express uncertainty is with a confidence interval. This is a predicted range of values that are likely to contain the true value a scientist is trying to find. Confidence intervals are usually expressed as percentages. With a 95-percent confidence interval, any new measurement should fall within that interval 95 times out of 100.
Uncertainty can also be used to indicate how likely something is to occur. For example, climate change scientists may include uncertainty in their discussions. This doesn’t mean that they are uncertain whether the planet’s climate is changing. They have documented that change in many ways. But there is always some small bit of uncertainty around how much change is happening and where.
In a sentence
When scientists study how much the nutrition value of a food changes over time, their results include the uncertainty around their measurements.
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climate The weather conditions that typically exist in one area, in general, or over a long period.
climate change Long-term, significant change in the climate of Earth. It can happen naturally or in response to human activities, including the burning of fossil fuels and clearing of forests.
confidence interval An estimated range of values — derived from a set of data — that are likely to contain the real value. This range is used to understand the amount of uncertainty in a sample of data. Confidence intervals are usually expressed in a percentage. For example, a 95 percent confidence interval means that in 95 tests out of 100, the result a scientist obtained would be within that range.
data Facts and/or statistics collected together for analysis but not necessarily organized in a way that gives them meaning. For digital information (the type stored by computers), those data typically are numbers stored in a binary code, portrayed as strings of zeros and ones.
error (In statistics) The non-deterministic (random) part of the relationship between two or more variables.
mean One of several measures of the “average size” of a data set. Most commonly used is the arithmetic mean, obtained by adding the data and dividing by the number of data points.
nutrition (adj. nutritious) The healthful components (nutrients) in the diet — such as proteins, fats, vitamins and minerals — that the body uses to grow and to fuel its processes. A scientist who works in this field is known as a nutritionist.
point (in mathematics) A precise point in space that is so small that it has no size. It merely has an address.
random Something that occurs haphazardly or without reason, based on no intention or purpose.
range The full extent or distribution of something. For instance, a plant or animal’s range is the area over which it naturally exists. (in math or for measurements) The extent to which variation in values is possible. Also, the distance within which something can be reached or perceived.
standard error of the mean (in statistics) The likely distribution of numbers in a data set, based on a random sample.
uncertainty A range of how much measurements of something are predicted to vary around an already-measured value.