What is defined as the degree of closeness of repeated measurements?

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Multiple Choice

What is defined as the degree of closeness of repeated measurements?

Explanation:
The term that best describes the degree of closeness of repeated measurements is precision. Precision refers to how consistent results are when the same measurement is taken multiple times under the same conditions. High precision means that the measurements produce very similar results to one another, regardless of whether those measurements are close to the actual or true value. When measurements are precise, they show little variability, indicating that the measuring process or instrument is reliable for producing consistent results. This contrasts with accuracy, which refers to the closeness of a measurement to the true or accepted value; thus, it is possible to have a set of measurements that are highly precise but not accurate if they are clustered around a value that is far from the true value. Measurement error generally refers to the difference between the measured value and the true value, while statistical significance pertains to the reliability of a result or finding in the context of statistical analysis.

The term that best describes the degree of closeness of repeated measurements is precision. Precision refers to how consistent results are when the same measurement is taken multiple times under the same conditions. High precision means that the measurements produce very similar results to one another, regardless of whether those measurements are close to the actual or true value.

When measurements are precise, they show little variability, indicating that the measuring process or instrument is reliable for producing consistent results. This contrasts with accuracy, which refers to the closeness of a measurement to the true or accepted value; thus, it is possible to have a set of measurements that are highly precise but not accurate if they are clustered around a value that is far from the true value.

Measurement error generally refers to the difference between the measured value and the true value, while statistical significance pertains to the reliability of a result or finding in the context of statistical analysis.

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