Free reference · 596 entries
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Short, plain definitions of the terms that turn up in statistics and data science — what they mean, and how they relate to each other. Nothing to sign in for.
41 of 596 entries under R
- R-squaredSee Coefficient of determination
- Random ErrorThe random error is the fluctuating part of the overall error that varies from measurement to measurement.
- Random FieldA random field describes an experiment with outcomes being functions of more than one continuous variable, for example U(x,y,z), where x, y, and z are coordinates in space.
- Random NumbersRandom numbers are the numbers produced by a truly random mechanism (in contrast to pseudo-random numbers).
- Random ProcessA random process describes an experiment with outcomes being functions of a single continuous variable (e.g.
- Random SamplingRandom sampling is a method of selecting a sample from a population in which all the items in the population have an equal chance of being chosen in the sample.
- Random SeriesA random series describes an experiment with outcomes being functions of an integer argument: U1, U2, … (or, simply, sequences of random values – 1st value, 2nd value, etc).
- Random VariableA random variable is a variable that takes different real values as a result of the outcomes of a random event or experiment.
- Random WalkA random walk is a process of random steps, motions, or transitions. It might be in one dimension (movement along a line), in two dimensions (movements in a plane), or in three dimensions or more.
- Randomization TestSee permutation tests.
- RangeRange is a measure of dispersion. It is defined as the difference between the highest and the lowest values.
- Rank Correlation CoefficientRank correlation is a method of finding the degree of association between two variables. The calculation for the rank correlation coefficient the same as that for the Pearson correlation coefficient, but is…
- Ratio ScaleA ratio scale is a measurement scale in which a certain distance along the scale means the same thing no matter where on the scale you are, and where “0” on the scale represents the absence of the thing…
- Reciprocal AveragingReciprocal averaging is a widely used algorithm for correspondence analysis. The correspondence analysis itself is sometimes also called reciprocal averaging.
- Rectangular FilterThe rectangular filter is the simplest linear filter; it is usually used as a smoother. The output of the rectangular filter at the time moment is the arithmetic mean of the input values corresponding to…
- Recursive FilterIn recursive filters, the output at the moment is a function of the output values at the previous moments and, probably, of the input values.
- RegressionSee regression analysis.
- Regression AnalysisRegression analysis provides a “best-fit” mathematical equation for the relationship between the dependent variable (response) and independent variable(s) (covariates).
- Regression TreesRegression trees is one of the CART techniques. The main distinction from classification trees (another CART technique) is that the dependent variable is continuous.
- RegularizationRegularization refers to a wide variety of techniques used to bring structure to statistical models in the face of data size, complexity and sparseness.
- Rejection RegionSee Acceptance region
- Relative Efficiency (of tests)The relative efficiency of two tests is a measure of the relative power of two tests. Suppose tests 1 and 2 are tests for the same null-hypothesis and at the same significance level “alpha” (probability of…
- Relative Frequency DistributionA relative frequency distribution is a tabular summary of a set of data showing the relative frequency of items in each of several non-overlapping classes.
- ReliabilityReliability characterises the capability of a device, unit, procedure to perform without fault.
- Reliability (in Survey Analysis)In survey analysis, e.g. in psychometrics, reliability is a measure of reproducibility of the survey instrument or test.
- RepeatabilityRepeatability is the variation of outcomes of an experiment carried out in the same conditions, e.g.
- Repeated Measures DataRepeated measures (or repeated measurements) data are usually obtained from multiple measurements of a response variable.
- ReplicateA replicate is the outcome of an experiment or observation obtained in course of its replication.
- ReplicationIn statistics, replication is repetition of an experiment or observation in the same or similar conditions.
- ReproducibilityReproducibility is the variation of outcomes of an experiment carried out in conditions varying within a typical range, e.g.
- ResamplingSee bootstrapping and permutation tests
- ResidualsResiduals are differences between the observed values and the values predicted by some model.
- ResistanceResistance, used with respect to sample estimators, refers to the sensitivity of the estimator to extreme observations.
- ResponseIn design of experiments, response is a dependent variable. Its values are measured for all subjects, and the question of primary interest is how factors affect the response.
- Response Variablesee dependent and independent variables
- RMSSee Root Mean Square.
- RMSERMSE is root mean squared error. In predicting a numerical outcome with a statistical model, predicted values rarely match actual outcomes exactly.
- Robust FilterA robust filter is a filter that is not sensitive to input noise values with extremely large magnitude (e.g.
- RobustnessMany statistical methods (particularly classical inference methods) rely upon assumptions about the distribution of the population the sample is drawn from.
- Root Mean SquareN 1 N ? i=1 xi2 RMS is a statistical measure of departure from the null value. If the symbols do not display properly, try the graphic version of this page
- Root Mean Square (Graphical)Root mean square (RMS) of a set of values xi, i=1,…N is the square root of the mean of the squares of the values: RMS is a statistical measure of departure from the null value.
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