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.
Drawing conclusions about population parameters from sample data. See https://en.wikipedia.org/wiki/Inference and https://en.wikipedia.org/wiki/Statistical_inference
Survival analysis models time to event data, typically time to death or failure time. Censored data are a common problem for survival analyses.
for any use of optimization within statistics.
The expected value of a random variable; or a location measure for a sample.
In frequentist hypothesis testing, the $p$-value is the probability of a result as extreme (or more) than the observed result, under the assumption that the null hypothesis is true.
Refers to a general estimation technique that selects the parameter value to minimize the squared difference between two quantities, such as the observed value of a variable, and the expected value of…
Repeated measures data occur when more than one measurement is collected on the same unit (e.g. subject). Use this tag for RM-ANOVA together with [anova] tag.
describes the process of creating a statistical or machine learning model. Always add a more specific tag.
A test (typically of distribution, independence, or goodness of fit), for the family of distributions use [chi-squared-distribution].
Questions seeking external references (books, papers, etc.) about a particular subject. Always use a more specific tag in addition.
Analyses where there is more than one variable analyzed together at once, and these variables are either dependent (response) ones or the only ones in the analysis. This can be contrasted with "multip…
Econometrics is a field of statistics dealing with applications to economics.
Random forest is a machine-learning method based on combining the outputs of many decision trees.
Mathematical re-expression, often nonlinear, of data values. Data are often transformed either to meet the assumptions of a statistical model or to make the results of an analysis more interpretable.
A situation where the effect of an explanatory variable may depend on the value of another explanatory variable.
Refers to any model where a random variable is related to one or more random variables by a function that is linear in a finite number of parameters.
Methods and principles of selecting a subset of attributes for use in further modelling
Support Vector Machine refers to "a set of related supervised learning methods that analyze data and recognize patterns, used for classification and regression analysis."
A random variable or stochastic variable is a value that is subject to chance variation (i.e., randomness in a mathematical sense).
The probability that an event A will occur, when another event B is known to occur or to have occurred. It is commonly denoted by P(A|B).
The binomial distribution gives the frequencies of "successes" in a fixed number of independent "trials". Use this tag for questions about data that might be binomially distributed or for questions a…
Refers generally to making substantive conclusions from the results of a statistical analysis.
Panel data refers to multi-dimensional data frequently involving measurements over time in econometrics. It is also called longitudinal data in biostatistics.
The expected value of a random variable is 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.
IBM SPSS Statistics is a statistical software package. Use this tag for any on-topic question that (a) involves SPSS either as a critical part of the question or expected answer and (b) is not just ab…
to ask about the nature of nonparametric or parametric methods, or the difference between the two. Nonparametric methods generally rely on few assumptions about the underlying distributio…
An area of machine learning concerned with learning hierarchical representations of the data, mainly done with deep neural networks.
Standard deviation is the square root of the variance of a random variable, an estimator thereof, or a similar measure of the spread of a batch of data.
Model selection is a problem of judging which model from some set performs best. Popular methods include $R^2$, AIC and BIC criteria, test sets, and cross-validation. To some extent, feature selection…
The parameters of a regression model. Most commonly, the values by which the independent variables will be multiplied to get the predicted value of the dependent variable.
Requests for datasets are off-topic on this site. Use this tag for questions concerning creating, processing, or maintaining datasets.
A discrete distribution defined on the non-negative integers that has the property that the mean is equal to the variance.
The bootstrap is a resampling method to estimate the sampling distribution of a statistic.
The study of how to structure an information-gathering exercise where variation is present.
very ambiguous. Use it when the question is about sample size and NONE of the following are more appropriate: [small-sample], [large-data], [power-analysis], [power], [underdetermined] or …
A vast area which includes generating results from computer models.