Free reference · 596 entries
The words, before the course.
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.
19 of 596 entries under H
- HadoopAs data processing requirements grew beyond the capacities of even large computers, distributed computing systems were developed to spread the load to multiple computers.
- Harmonic MeanHarmonic mean is a measure of central location. The harmonic mean of positive values is defined by the formula Let the path between two cities and be divided into parts of equal length.
- Hazard FunctionIn medical statistics, the hazard function is a relationship between a proportion and time.
- Hazard RateSee Hazard function
- HDFSHDFS is the Hadoop Distributed File System. It is designed to accommodate parallel processing on clusters of commodity hardware, and to be fault tolerant.
- HeteroscedasticityHeteroscedasticity generally means unequal variation of data, e.g. unequal variance. For special cases see heteroscedasticity in regression, heteroscedasticity in hypothesis testing
- Heteroscedasticity in hypothesis testingIn hypothesis testing, heteroscedasticity means a situation in which the variance is different for compared samples.
- Heteroscedasticity in regressionIn regression analysis, heteroscedasticity means a situation in which the variance of the dependent variable varies across the data.
- Hierarchical Cluster AnalysisHierarchical cluster analysis (or hierarchical clustering) is a general approach to cluster analysis, in which the object is to group together objects or records that are “close” to one another.
- HistogramA histogram is a graph of a dataset, composed of a series of rectangles. The width of these rectangles is proportional to the range of values in a class or bin, all bins being the same width.
- Hold-Out SampleA hold-out sample is a random sample from a data set that is withheld and not used in the model fitting process.
- HomoscedasticityHomoscedasticity generally means equal variation of data, e.g. equal variance. For special cases see homoscedasticity in regression, homoscedasticity in hypothesis testing
- Homoscedasticity in hypothesis testingIn hypothesis testing, homoscedasticity means a situation in which the variance is the same for all the compared samples.
- Homoscedasticity in regressionIn regression analysis, homoscedasticity means a situation in which the variance of the dependent variable is the same for all the data.
- Hotelling Trace CoefficientThe Hotelling Trace coefficient (also called Lawley-Hotelling or Hotelling-Lawley Trace) is a statistic for a multivariate test of mean differences between two groups.
- Hotelling-Lawley TraceSee Hotelling Trace coefficient.
- Hotelling’s T-SquareHotelling’s T-square is a statistic for a multivariate test of differences between the mean values of two groups.
- HypothesisA (statistical) hypothesis is an assertion or conjecture about the distribution of one or more random variables.
- Hypothesis TestingHypothesis testing (also called “significance testing”) is a statistical procedure for discriminating between two statistical hypotheses – the null hypothesis (H0) and the alternative hypothesis ( Ha, often…
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