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The central value for a set of measurements is usually the same as the individual results.
The central value for a set of measurements is usually the same as the individual results.
False
The mean and the median are both used as measures of central value.
The mean and the median are both used as measures of central value.
True
The median is the average value of all the results in a set.
The median is the average value of all the results in a set.
False
When there is an odd number of results, the median is the middle result when data are arranged in order.
When there is an odd number of results, the median is the middle result when data are arranged in order.
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Replicates in a sample are not important for determining the reliability of results.
Replicates in a sample are not important for determining the reliability of results.
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The mean is calculated by summing up all replicate measurements and multiplying them by the number of measurements.
The mean is calculated by summing up all replicate measurements and multiplying them by the number of measurements.
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Precision measures the closeness of results obtained in different ways.
Precision measures the closeness of results obtained in different ways.
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Accuracy indicates the agreement between a measurement result and the true value.
Accuracy indicates the agreement between a measurement result and the true value.
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Random error causes data to be scattered symmetrically around the mean value.
Random error causes data to be scattered symmetrically around the mean value.
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Systematic errors may be either random or indeterminate.
Systematic errors may be either random or indeterminate.
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Personal errors in measurements require personal judgments.
Personal errors in measurements require personal judgments.
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Constant errors become less serious as the size of the quantity measured decreases.
Constant errors become less serious as the size of the quantity measured decreases.
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Proportional errors are caused by the presence of interfering contaminants in the sample.
Proportional errors are caused by the presence of interfering contaminants in the sample.
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The effect of solubility losses is an example of proportional errors.
The effect of solubility losses is an example of proportional errors.
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Accuracy is expressed in terms of absolute error only.
Accuracy is expressed in terms of absolute error only.
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Systematic method errors are introduced by instrumental errors.
Systematic method errors are introduced by instrumental errors.
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