A tag is a keyword or label that categorizes your question with other, similar questions. Using the right tags makes it easier for others to find and answer your question.

Type to find tags:
× 160
Shifting and rescaling data to assure zero mean and unit variance.
× 159
A discrete, univariate distribution modelling the number of ${\rm Bernoulli}(p)$ trial successes until a specified number of failures occur.
× 159
Robustness in general refers to a statistic's insensitivity to deviations from its underlying assumptions (Huber and Ronchetti, 2009).
× 159
× 158
ordering data from highest to lowest or *vice versa.* For questions about *constructing* scores to use in ranking, please use the "valuation" tag, too.
× 157
'Large data' refers to situations where the number of observations (data points) is so large that it necessitates changes in the way the data analyst thinks about or conducts the analysis. (Not to be …
× 155
Generalized Linear Mixed (effects) Models are typically used for modeling non-independent non-normal data (eg, longitudinal binary data).
× 155
The science of statistics applied to the analysis of biological or medical data.
× 154 × 154
Distance functions refer to functions used for quantifying the notion of distance between members of a set, or between objects.
× 154
a graphical representation of the frequencies of a continuous variable. The variable is divided into bins and a bar is drawn for each bin, proportional to its frequency in the data.
× 154
A non-negative continuous probability distribution indexed by two strictly positive parameters.
× 154
a test for goodness of fit of data to a distribution. It is often used to test whether a variable is normally distributed.
× 153
Refers to data generated from a distribution that has a countable sample space. Discrete data may be nominal (e.g. the distribution of race in a sample of individuals) or ordinal (e.g. the number of e…
× 153
called continuous if its set of possible values is uncountable, and the chance that it takes any particular value is zero ($\text{P}(X = x) = 0$ for every real number $x$). A …
× 152
Average most often refers to the arithmetic mean, but more generally to measures of central tendency that use most, or all, of the data values. Examples include trimmed mean, Winsorized mean, harmonic…
× 152
decided upon after the data has been collected, as opposed to "a priori".
× 151
Refers to any statistical complication or problem due to having few data.
× 151
"Mixed effects models" refers to models that have both fixed effects and random effects. They are used to model longitudinal data or data that are clustered & thus do not have independent errors.
× 150
Convergence generally means that a sequence of a certain sample quantity approaches a constant as the sample size tends to infinity.
× 150
Psychometrics has evolved as a subfield of psychology to become the science of measurement of unobservable individual characteristics.
× 148
The quantiles of a distribution refer to points on its cumulative distribution function. Some common quantiles are quartiles and percentiles.
× 145
Refers to the probability distribution of parameters conditioned on data in Bayesian statistics.
× 144
one that is written as a convex combination of other distributions.
× 144
A distribution describing the time between events in a Poisson process; a continuous analogue of the geometric distribution.
× 143
Refers to techniques for classifying data into categories based on similarities (which can either be known previously, or learned).
× 141
collected repeatedly on the same subjects. When there is a long series of data, time series analysis may be appropriate. For shorter series, mixed models (a…
× 140
× 140
Skewness measures (or refers to) a degree of asymmetry in the distribution of a variable.
× 139
the distribution of a random variable whose logarithm has a normal distribution.
× 139
Descriptive statistics summarize features of a sample, such as mean and standard deviations, median and quartiles, the maximum and minimum. With multiple variables, may include correlations and crosst…
× 139
Causal inference tries to quantify the effect of a change in $X$ on $Y$ whilst holding constant or eliminating all other relevant factors which might influence this relationship.
× 138
A mathematical quantity designed to measure the amount of randomness of a random variable.
× 138
one whose joint distribution is constant over time. A weakly stationary process or series is one whose mean and covariance function (variance and autocorrelati…
× 138
the process of assessing whether the results of an analysis are likely to hold outside of the original research setting. DO NOT use this tag for discussing `validity` of a measurement or…
× 135
the study of the distribution and spread of disease or illness at the population level.