Best Answer

You may be referring to the statistical term 'outlier(s)'. Also, there is a rule in statistics called the '68-95-99 Rule'. It states that in a normally distributed dataset approximately 68% of the observations will be within plus/minus one standard deviation of the mean, 95% within plus/minus two standard deviations, and 99% within plus/minus three standard deviations. So if your data follow the classic bell-shaped curve, roughly 1% of the measures should fall beyond three standard deviations of the mean.

🙏

🤨

😮

Study guides

☆☆

Q: What is the measures that fall beyond three standard deviations of the mean called?

Write your answer...

Submit

Still have questions?

Related questions

Outliers

Extreme values. They might also be called outliers but there is no agreed definition for the term "outlier".

They are observations with a low likelihood of occurrence. They may be called outliers but there is no agreed definition for outliers.

It is a measurement which may, sometimes, be called an extreme observation or an outlier. However, there is no agreed definition for outliers.

It is not called anything special, just 2 standard deviations or 3 sd.

The international standard is called A4. It measures 8.27 inches by 11.7 inches. The North American standard is called "Letter." It measures 8.5 inches by 11 inches.

Values that are either extremely high or low in a data set are called 'outliers'. They are typically 3 standard deviations or more from the mean.

Megalencephaly (also called macrencephaly) describes an enlarged brain whose weight exceeds the mean (the average weight for that age and sex) by at least 2.5 standard deviations (a statistical measure of variation).

Measurements. Just because a particular result lies far from the mean doesn't make it any different. If it's noticeably far from the "crowd" of all the other measurements, it can be called an outlier. An outlier isn't necessarily bad, just different. It should be examined in detail to see if there's something odd about it, but not discarded out of hand.

The mean deviation (also called the mean absolute deviation) is the mean of the absolute deviations of a set of data about the data's mean. The standard deviation sigma of a probability distribution is defined as the square root of the variance sigma^2,

Generally not without further reason. Extreme values are often called outliers. Eliminating unusually high values will lower the standard deviation. You may want to calculate standard deviations with and without the extreme values to identify their impact on calculations. See related link for additional discussion.

The burden of proof is "beyond a reasonable doubt" in all criminal trials. In civil trials, the burden of proof is either "a preponderance of the evidence" or "proof by clear and convincing evidence." The "clear and convincing evidence" standard is called for in certain types of cases where there is a need for a higher level of proof than "the preponderance of the evidence" standard. The "clear and convincing evidence standard is not as heavy as "beyond a reasonable doubt."

The technology which is called total factor productivity. It measures the efficiency of all inputs to a production process.

Meter organizes stressed and unstressed sounds into units called measures.

In a car it is called an odometer.An 'Odometer' measures mileage.

A hygrometer measures humidity. Don't confuse it with a hydrometer which measures density.

Meter organizes stressed and unstressed sounds into units called measures.

If it measures 90 degrees, then it is called a right angle.

monitoring level

Ok so basically the chebyshev's theorem states that 75% of your data will lie within 2 standard deviations of the mean and that 89% of your data will lie within 3 standard deviations of the mean. And I believe that this theorem is much more precise than the Empirical Rule, which assumes normality and can be off. I am currently taking a stats. class if I didn't help or my wording is unclear please let me know. Also any information here was obtained or learned from the book called Elementary Statistics by Mario F. Triola

Using 'a raft of' preceding a noun is a term for a 'large quantity' of that thing.

Optometrists

a newton

Obtuse.

Ells