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
Refers to the AutoRegressive Integrated Moving Average model used in time series modeling both for data description and for forecasting. This model generalizes the ARMA model by including a term for d…
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.
The expected value of a random variable; or a location measure for a sample.
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…
for any use of optimization within statistics.
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.
A test (typically of distribution, independence, or goodness of fit), for the family of distributions use [chi-squared-distribution].
A situation where the effect of an explanatory variable may depend on the value of another explanatory variable.
Questions seeking external references (books, papers, etc.) about a particular subject. Always use a more specific tag in addition.
describes the process of creating a statistical or machine learning model. Always add a more specific tag.
Econometrics is a field of statistics dealing with applications to economics.
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.
Analyses/models where there is more than one response (dependent) variable. Commonly confused with "multiple" or "multivariable" analysis, which has more than one predictor (independent) variable.
Random forest is a machine-learning method based on combining the outputs of many decision trees.
A random variable or stochastic variable is a value that is subject to chance variation (i.e., randomness in a mathematical sense).
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.
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).
Refers generally to making substantive conclusions from the results of a statistical analysis.
Methods and principles of selecting a subset of attributes for use in further modelling
Panel data refers to multi-dimensional data frequently involving measurements over time in econometrics. It is also called longitudinal data in biostatistics.
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…
Support Vector Machine refers to "a set of related supervised learning methods that analyze data and recognize patterns, used for classification and regression analysis."
2283 questions
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.
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…
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.
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…
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 study of how to structure an information-gathering exercise where variation is present.
The bootstrap is a resampling method to estimate the sampling distribution of a statistic.
Requests for datasets are off-topic on this site. Use this tag for questions concerning creating, processing, or maintaining datasets.
ambiguous. Use it when the question is about sample size and NONE of the following are more appropriate: [small-sample], [large-data], [statistical-power], [underdetermined], or [unbalance…
A vast area which includes generating results from computer models.
An area of machine learning concerned with learning hierarchical representations of the data, mainly done with deep neural networks.
1870 questions
A discrete distribution defined on the non-negative integers that has the property that the mean is equal to the variance.
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