On a method of robust standardization

The empirical rule, also known as the three-sigma rule, allows a statistician to interpret the standard deviation in a normally distributed dataset. The rule states that 68% of the data lies within one standard deviation from the mean, 95% lies within two standard deviations from the mean, and 99.7% lies within three standard deviations from the mean. Additionally, this rule is also called the 68-95-99.7 rule.
This rule is used widely in statistics to calculate the proportion of data values...

A physical quantity is defined either by specifying its measurement method or by stating how it is calculated from other measurements. For example, consider a metallic cube. We might define its mass and dimensions by specifying methods for measuring them, such as using a weighing machine and a meter scale. Then, we could define the volume by stating that it is the cube of its side, and we could calculate the density as the mass divided by the volume.
Measurements of physical quantities are...

A physical quantity is defined either by specifying its measurement method or by stating how it is calculated from other measurements. For example, consider a metallic cube. We might define its mass and dimensions by specifying methods for measuring them, such as using a weighing machine and a meter scale. Then, we could define the volume by stating that it is the cube of its side, and we could calculate the density as the mass divided by the volume.
Measurements of physical quantities are...

The range rule of thumb in statistics helps us calculate a dataset's minimum and maximum values with known standard deviation. This rule is based on the concept that 95% of all values in a dataset lie within two standard deviations from the mean.
For instance, the range rule of thumb can be used to find the tallest and the shortest student in a class, given the mean student height and standard deviation. If the mean student height is 1.6 m and the standard deviation, s is 0.05 m, the height of...

Every measurement provides three kinds of information: the size or magnitude of the measurement (a number), a standard of comparison for the measurement (a unit), and an indication of the uncertainty of the measurement. While the number and unit are explicitly represented when a quantity is written, the uncertainty is an aspect of the errors in the measurement results.

To construct a confidence interval for a single unknown population mean μ, where the population standard deviation is known, we need sample mean as an estimate for μ and we need the margin of error. Here, the margin of error (EBM) is called the error bound for a population mean (abbreviated EBM). The sample mean is the point estimate of the unknown population mean μ.
The confidence interval estimate will have the form as follows:
(point estimate - error bound, point estimate + error bound)
The...