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  2. Best–worst scaling - Wikipedia

    en.wikipedia.org/wiki/Best–worst_scaling

    In general with BWS, survey respondents are shown a subset of items from a master list and are asked to indicate the best and worst items (or most and least important, or most and least appealing, etc.). The task is repeated a number of times, varying the particular subset of items in a systematic way, typically according to a statistical ...

  3. Mallows's Cp - Wikipedia

    en.wikipedia.org/wiki/Mallows's_Cp

    In statistics, Mallows's, [1] [2] named for Colin Lingwood Mallows, is used to assess the fit of a regression model that has been estimated using ordinary least squares.It is applied in the context of model selection, where a number of predictor variables are available for predicting some outcome, and the goal is to find the best model involving a subset of these predictors.

  4. Cluster analysis - Wikipedia

    en.wikipedia.org/wiki/Cluster_analysis

    Graph-based model s: a clique, that is, a subset of nodes in a graph such that every two nodes in the subset are connected by an edge can be considered as a prototypical form of cluster. Relaxations of the complete connectivity requirement (a fraction of the edges can be missing) are known as quasi-cliques, as in the HCS clustering algorithm .

  5. Hosmer–Lemeshow test - Wikipedia

    en.wikipedia.org/wiki/Hosmer–Lemeshow_test

    The Hosmer–Lemeshow test is a statistical test for goodness of fit and calibration for logistic regression models. It is used frequently in risk prediction models. The test assesses whether or not the observed event rates match expected event rates in subgroups of the model population.

  6. Multiple comparisons problem - Wikipedia

    en.wikipedia.org/wiki/Multiple_comparisons_problem

    In statistics, the multiple comparisons, multiplicity or multiple testing problem occurs when one considers a set of statistical inferences simultaneously [1] or estimates a subset of parameters selected based on the observed values. [2] The larger the number of inferences made, the more likely erroneous inferences become.

  7. Rand index - Wikipedia

    en.wikipedia.org/wiki/Rand_index

    Example clusterings for a dataset with the kMeans (left) and Mean shift (right) algorithms. The calculated Adjusted Rand index for these two clusterings is . The Rand index [1] or Rand measure (named after William M. Rand) in statistics, and in particular in data clustering, is a measure of the similarity between two data clusterings.

  8. NYT ‘Connections’ Hints and Answers Today, Friday, December 13

    www.aol.com/nyt-connections-hints-answers-today...

    If you've been having trouble with any of the connections or words in Friday's puzzle, you're not alone and these hints should definitely help you out. Plus, I'll reveal the answers further down ...

  9. Tukey's range test - Wikipedia

    en.wikipedia.org/wiki/Tukey's_range_test

    Tukey's range test, also known as Tukey's test, Tukey method, Tukey's honest significance test, or Tukey's HSD (honestly significant difference) test, [1] is a single-step multiple comparison procedure and statistical test.