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.
22 of 596 entries under T
- t-distributionA continuous distribution, with single peaked probability density symmetrical around the null value and a bell-curve shape.
- t-distribution (Graphical)A continuous distribution, with single peaked probability density symmetrical around the null value and a bell-curve shape.
- t-statisticT-statistic is a statistic whose sampling distribution is a t-distribution. where and are the mean and the standard deviation of the sample.
- t-statistic (Graphical)T-statistic is a statistic whose sampling distribution is a t-distribution. where and are the mean and the standard deviation of the sample.
- t-testA t-test is a statistical hypothesis test based on a test statistic whose sampling distribution is a t-distribution.
- Target VariableSee dependent and independent variables
- Test SetA test set is a portion of a data set used in data mining to assess the likely future performance of a single prediction or classification model that has been selected from among competing models, based on…
- Test-Retest ReliabilityThe test-retest reliability of a survey instrument, like a psychological test, is estimated by performing the same survey with the same respondents at different moments of time.
- The Tukey Mean-Difference PlotThe Tukey mean-difference plot is a scatter graph produced not for (x,y) values themselves, but for modified coordinates (X,Y) 2 X = (x+y) , Y = y–x.
- Time SeriesTime series data are measurements of a variable taken at regular intervals over time. Time series are represented as sequences of values like x(1), x(2), … .
- Time Series AnalysisTime series analysis is a branch of statistics dealing with data represented as time series.
- Time-series dataSee longitudinal data
- TokenizationIn processing unstructured text, tokenization is the step by which the character string in a text segment is turned into units – tokens – for further analysis.
- Training SetA training set is a portion of a data set used to fit (train) a model for prediction or classification of values that are known in the training set, but unknown in other (future) data.
- TransformationTransformation is the conversion of a data set into a transformed data set by the application of a function.
- Triangular FilterThe triangular filter is a linear filter that is usually used as a smoother. The output of the rectangular filter at the moment is the weighted mean of the input values at the adjacent moments of discrete…
- Trimmed MeanThe trimmed mean is a family of measures of central tendency. The -trimmed mean of of values is computed by sorting all the values, discarding % of the smallest and % of the largest values, and computing…
- TruncationTruncation, generally speaking, means to shorten. In statistics it can mean the process of limiting consideration or analysis to data that meet certain criteria (for example, the patients still alive at a…
- Tukey’s HSD (Honestly Significant Differences) TestThis test is used for testing the significance of unplanned pairwise comparisons. When you do multiple significance tests, the chance of finding a “significant” difference just by chance increases.
- Two-Tailed TestA two-tailed test is a hypothesis test in which the null hypothesis is rejected if the observed sample statistic is more extreme than the critical value in either direction (higher than the positive…
- Type I ErrorIn a test of significance, Type I error is the error of rejecting the null hypothesis when it is true — of saying an effect or event is statistically significant when it is not.
- Type II ErrorIn a test of significance, Type II error is the error of accepting the null hypothesis when it is false — of failing to declare a real difference as statistically significant.
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