# Tags

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:
 autocorrelation× 589 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. simulation× 585 A vast area which includes generating results from computer models. multilevel-analysis× 575 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… factor-analysis× 560 a data reduction technique which replaces inter-correlating variables by a smaller number of continuous latent variables called factors. The factors are believed to be responsible f… standard-error× 559 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 … missing-data× 556 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. pdf× 547 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… regression-coefficients× 546 The parameters of a regression model. survey× 544 collect a sample from a population. Surveying often refers to sampling of human populations and is primarily done by administering questionnaires or interviewing indivi… inference× 544 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… outliers× 542 an observation that appears to be unusual or not well described relative to a simple characterization of a dataset. A discomfiting possibility is that these data come from a different po… expected-value× 537 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. mcmc× 532 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… ordinal× 511 ordinal refers to data that have an order but not necessarily equal spacing between levels. It can also refer to ordinal logistic regression. goodness-of-fit× 493 Goodness of fit tests indicate whether or not it is reasonable to assume that a random sample comes from a specific distribution. residuals× 488 the actual values minus the predicted values. Many statistical models make assumptions about the error, which is estimated by the residuals. random-effects-model× 485 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… sas× 474 a proprietary cross-platform general-purpose statistical software package. [Official Website](http://www.sas.com/index.html) model× 474 a formalization of relationships between variables in the form of mathematical equations. The model is statistical as the variables are not deterministically but stochastically … cart× 474 'Classification And Regression Trees'. CART is a popular data mining technique. binary-data× 472 A binary variable takes one of two values, typically coded as "0" and "1". nonlinear-regression× 447 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*). lmer× 444 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… algorithms× 443 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 … terminology× 443 Indicates questions asking about the use and meaning of specific technical words/concepts in statistics. stochastic-processes× 436 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… proportion× 430 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. normalization× 430 A way of re-expressing data to make their values lie within a specified range. cox-model× 430 a very popular, semi-parametric method for survival analysis. heteroscedasticity× 414 Non-constant variance along some continuum in a random process. multinomial× 414 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. error× 411 the deviation of the observed value from the (unobservable) true function value. Do NOT use this tag for SOFTWARE ERROR messages. monte-carlo× 410 Using (pseudo-)random numbers and the Law of Large Numbers to simulate the random behavior of a real system. independence× 408 independent when information on some of them tells you nothing about the probability of occurrence (/ distribution) of the others. Please DO NOT use this tag for indep… k-means× 398 a family of cluster analysis methods in which you specify the number of clusters you expect. This is as opposed to hierarchical cluster analysis methods. lasso× 393 A regularization method for regression models that shrinks coefficients towards zero, making some of them equal to zero. Thus lasso performs feature selection.