# 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:
 r× 11474 for any *on-topic* question that (a) involves R either as a critical part of the question or expected answer (b) is not *just* about how to use R. regression× 8943 Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables. machine-learning× 4374 Methods and principles of building "computer systems that automatically improve with experience." time-series× 4363 data observed over time (either in continuous time or at discrete time periods). probability× 3319 A probability provides a quantitative description of the likely occurrence of a particular event. hypothesis-testing× 3133 Hypothesis testing assesses whether data support a given hypothesis rather than being an effect of random fluctuations or some other process described by an alternative hypothesis. self-study× 3024 A routine question from a textbook, course, or test used for a class or self-study. This community's policy is to "provide helpful hints" for self-study questions. distributions× 2761 a mathematical description of probabilities or frequencies. logistic× 2712 Refers generally to statistical procedures that utilize the logistic function, most commonly various forms of logistic regression correlation× 2435 A measure of the degree of linear association among a pair of variables. classification× 2193 the problem of identifying the sub-population to which new observations belong, where the identity of the sub-population is unknown, on the basis of a training set of dat… statistical-significance× 2162 Statistical significance refers to the probability that, if, in the population from which this sample were drawn the true effect were 0 (or some hypothesized value) a test statistic as extreme or more… bayesian× 2089 a method of statistical inference that relies on turning the model parameters into random variables and applying Bayes' theorem to deduce probability statements about the paramet… anova× 2063 ANOVA stands for ANalysis Of VAriance, a statistical model and set of procedures for comparing multiple group means. The independent variables in an ANOVA model are categorical, but an ANOVA table can… normal-distribution× 1811 The normal, or Gaussian, distribution has a density function that is a symmetrical bell-shaped curve. It is often used as a reference against which other distributions are compared. clustering× 1651 Partitioning data into subsets of objects according to their mutual "similarity," without using preexisting knowledge such as class labels. Clustered-standard-errors and/or cluster-samples should be t… multiple-regression× 1624 Regression that includes two or more non-constant independent variables. mathematical-statistics× 1538 Mathematical theory of statistics, concerned with formal definitions and general results. mixed-model× 1530 Linear models that include both fixed effects and random effects. They are used to model longitudinal or nested data; such data do not have independent errors and mixed models can account for the aris… confidence-interval× 1455 An interval of random variables, depending on observed data, which, with a fixed probability, contain an unknown parameter of interest. categorical-data× 1390 Categorical data can take on a limited (usually fixed) number of possible values called categories. Categorical values "label", they do not "measure". Nominal and dichotomous/binary scale types are ca… data-visualization× 1364 Constructing meaningful and useful graphical representations of data. (If your question is only about how to get particular software to produce a specific effect, then it is likely not on topic here.) estimation× 1293 Any statistical process which seeks to approximate an unknown value, such as a distribution, a point estimate (e.g. mean), or confidence interval. generalized-linear-model× 1284 A generalization of linear regression allowing for nonlinear relationships via a "link function" and for the variance of the response to depend on the predicted value. (Not to be confused with "genera… variance× 1244 The expected squared deviation of a random variable from its mean; or, the average squared deviation of data about their mean. spss× 1178 SPSS (Statistical Package for the Social Sciences) is a proprietary cross-platform general-purpose statistical software package. neural-networks× 1133 composed of 'neurons' - programming constructs that mimic the properties of biological neurons. A set of weighted connections between the neurons allows informati… pca× 1131 a technique to decompose an array of numerical data into a set of orthogonal vectors (uncorrelated linear combinations of the variables) called principal components. Th… sampling× 1123 Creating samples from a well-specified population using a probabilistic method and/or producing random numbers from a specified distribution. repeated-measures× 1118 Repeated measures data occurs when more than one measurement is collected on the same unit (e.g. subject). This data cannot be analysed through normal methods because the rows in the data are not inde… t-test× 1113 A test for comparing the means of two samples, or the mean of one sample (or even parameter estimates) with a specified value; also known as the "Student t-test" after the pseudonym of its inventor. svm× 1065 Support Vector Machine refers to "a set of related supervised learning methods that analyze data and recognize patterns, used for classification and regression analysis." forecasting× 1060 Forecasting involves estimating the value or distribution of a random variable which has not yet been observed. chi-squared× 1003 A test (typically of distribution, independence, or goodness of fit) or a family of distributions related to such a test. cross-validation× 985 Refers to general procedures that attempt to determine the generalizability of a statistical result. Cross-validation arises frequently in the context of assessing how a particular model fit predicts … maximum-likelihood× 962 a method of estimating parameters of a statistical model by choosing the parameter value that optimizes the probability of observing the given sample.