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:
× 406
Refers to the standard deviation of the sampling distribution of a statistic calculated from a sample. Standard errors are often required when forming confidence intervals or testing hypotheses about …
× 394
a quantity used to measure the strength and direction of the linear relationship between two variables. The covariance is unscaled, & thus often difficult to interpret; when scaled by th…
× 391
When the data present lack of information (gaps), i.e., are not complete. Hence, it is important to consider this feature when performing a analysis or test.
× 385
a value that is subject to chance variation (i.e., randomness in a mathematical sense).
× 385
A vast area which includes generating results from computer models.
× 379
Markov Chain Monte Carlo (MCMC) refers to a class of methods for generating samples from a target distribution by generating random numbers from a Markov Chain whose stationary distribution is the tar…
× 376
PDF stands for Probability Density Function. The PDF of a variable gives the relative probability for each value of a continuous variable. Use this tag when asking about probability functions in gener…
× 376
a proprietary cross-platform general-purpose statistical software package. [Official Website](http://www.sas.com/index.html)
× 371
Statistical methods appropriate for the analysis of data sets comprising several levels of hierarchy of units of analysis (e.g., students nested in classes nested in schools; observations nested in pa…
× 367
an observation that appears to be unusual or not well described relative to a simple characterization of a dataset.
× 364
the correlation of a series of data with itself at some lag. This is an important topic particularly in the analysis of time-series data.
× 359
`ordinal` refers to data that have an order but not necessarily equal spacing between levels. It can also refer to ordinal logistic regression.
× 357
Inference, in a statistical context, refers to drawing conclusions from data containing an element of randomness introduced by e.g. measurement error, sampling variation, or assignment of experimental…
× 343
the actual values minus the predicted values. Many statistical models make assumptions about the error, which is estimated by the residuals.
× 342
Parameters associated with the particular levels of a covariate are sometimes called the “effects” of the levels. If the levels that are observed represent a random sample from the set of all possible…
× 336
Goodness of fit tests indicate whether or not it is reasonable to assume that a random sample comes from a specific distribution.
× 333
a a set of one or more computations that will produce a calculated result. All statistics methods are algorithms. Algorithms can be simple, such as calculating a percentage, or can be …
× 331
a weighted average of all possible values a random variable can take on, with the weights equal to the probability of taking on that value.
× 319
The parameters of a regression model.
× 317
functions in the R package lme4 that fit mixed effects models (ie, models that include fixed & random effects). These models can be non-linear in the sense that the…
× 308
'Classification And Regression Trees'. CART is a popular data mining technique.
× 298
Non-constant variance along some continuum in a random process.
× 298
the fraction of some total that is of a particular kind, either (i) as a count of one type of thing out of a total count, or (ii) as a component of a continuous variable.
× 297
only for regression models (q.v.) in which the response is a nonlinear functions of the *parameters* (not because it's a nonlinear function of the *predictors*).
× 294
A stochastic process describes evolution of random variables/systems over time and/or space and/or any other index set. It has applications in areas such as econometrics, weather, signal processing, e…
× 293
a formalization of relationships between variables in the form of mathematical equations. The model is statistical as the variables are not deterministically but stochastically …
× 289
A multivariate, discrete probability distribution used to describe the results of a random experiment where each of $n$ outcomes are placed into one of $k$ nominal categories.
× 281
Refers to a subset of data mining concerned with extracting information from data in the form of text by recognizing patterns. The goal of text mining is often to classify a given document into one of…
× 278
the deviation of the observed value from the (unobservable) true function value. Do NOT use this tag for SOFTWARE ERROR messages.
× 277
A way of re-expressing data to make their values lie between 0 and 1 (or 0% and 100%).
× 273
a very popular, semi-parametric method for survival analysis.
× 271
Using (pseudo-)random numbers to simulate the random behavior of a real system.
× 270
Indicates questions asking about the use and meaning of specific technical words/concepts in statistics.
× 265
A form of regularization used in the estimation of regression coefficients that shrinks coefficient estimates by penalizing their absolute value (i.e. the $L_1$ norm of the estimates). Some coefficien…
× 263
Classically, a Likert scale was composed of the sum of many Likert items (ordinal ratings of the amount of agreement with a statement), where all the items were equally valid. Today the term sometimes…
× 261
The field of study concerning statistical methods that use space and spatial relationships (such as distance, area, volume, length, height, orientation, centrality and/or other spatial characteristics…