D

• Deviation – the difference between the observed values and the estimate of location.

E

• An experiment is the process by which an observation is made. In probability theory, an experiment or trial is any procedure that can be infinitely repeated and has a well-defined set of possible outcomes, known as the sample space. An experiment is said to be random if it has more than one possible outcome, and deterministic if it has only one.
• Extrapolation: inferring unknown values from trends in the known data

I

• Interquartile range – the difference between the 75th percentile and the 25th percentile

L

• Law of Large Numbers – a theorem that states that if an experiment is repeated a large number of times, then the averaged result should be close to the expected value.

M

• Mean – the sum of all values divided by the number of values, also called the average.
• Mean absolute deviation – the mean of the absolute values of the deviations from the mean.
• Median – the value such that one-half of the data lies above and below.
  • Another phrase for this value is the 50th percentile.
  • A percentile is the value such that P percent of the data lies below. Another term for this is quantile
• Median absolute deviations from the median – the median of the absolute values of the deviations from the median.

O

• Order statistics – metrics based on the data values sorted from the smallest to biggest.
• Outlier – An outlier is a data value that is very different from most of the data

R

• A random variable is a real-valued function for which the domain is a sample space.
  • A random variable Y is said to be discrete if it can assume only a finite or countably infinite1 number of distinct values.
• Range – the difference between the largest and the smallest value in the data set
• Robust – Not sensitive to extreme values
  • Another term for extreme value is outlier.
  • An outlier is a data value that is very different from most of the data

S

• The sample space associated with an experiment is the set consisting of all possible sample points. A sample space will be denoted by S.
  • A discrete sample space is one that contains either a finite or a countable number of distinct sample points. An event in a discrete sample space S is a collection of sample points—that is, any subset of S.
• A simple event is an event that cannot be decomposed. Each simple event corresponds to one and only one sample point. The letter A with a subscript will be used to denote a simple event or the corresponding sample point.
• Standard deviation – the square root of the variance

T

• Trimmed mean, or truncated mean – the average of all values after dropping a fixed number of extreme values

V

• Variance – the sum of squared deviations from the mean divided by n-1,  where n is the number of observations.

W

• Weighted mean – The sum of all values times a weight divided by the sum of the weights, and like the mean is known as the average, this can be referred to as the weighted average.
• Weighted median – the value such that 1/2 of the sum of the weights lies above and below the sorted data