Introduction for Treatment of Data

A key component of scientific analysis is the repeatability of experiments. We

want to get consistent results when trials are repeated and also understand how

much variability exists in the measurements. Accomplishing both repeatability

and gaining an understanding of how much measurements will vary from one

experiment to the next are key to the scientific process.

Accuracy and Precision

Whenever we take measurements we are generally concerned with the quality of

those measurements. We define the quality of the measurement using precision

and accuracy measures. In your Introductory Chemistry courses at Millersville

University, we will define the precision of a measurement using Relative Average

Deviation and accuracy using Relative Error.

Accuracy is a measure of how close we are to the “true” value. Sometimes we

know the true value, and sometimes we do not know the true value.

Precision is a measure of the repeatability of our measurements. An experiment

with high precision means that all the results are close to each other. An

experiment with low precision has not very repeatable results.

Average Value

Since we want to understand the repeatability of experiments, we will often

repeat an experiment many times. This repetition allows us to see the

consistency or lack of consistency in our results. A key result of those many

measurements is the average value. An average is found by adding the results

from all the trials and dividing by the total number of trials.

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Figure 2.3: 1.6: Measurement Uncertainty, Accuracy, and Precision is shared under a CC BY 4.0

license and was authored, remixed, and/or curated by OpenStax