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Data driven statistical methods
Peter Sprent
- 01 Jan 1998
63
TL;DR: This paper presents a meta-modelling procedure called Bootstrap-Driven Inference, which automates the very labor-intensive and therefore time-heavy and expensive process of manually cataloging and inferring the values of parameters in a data set.
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Abstract: Data-Driven Inference. The Bootstrap. Outliers, Contamination, and Robustness. Location Tests for Two Independent Samples. More One- and Two-Sample Tests. Three or More Independent Samples. Designed Experiments. Correlation and Concordance. Bivariate Regression. Other Regression Models and Diagnostics. Categorical Data Analysis. Further Categorical Data Analysis. Data-Driven or Model-Driven? References. Index.
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Citations
Controlling the risk of spurious findings from meta-regression.
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Mann-Whitney test is not just a test of medians: differences in spread can be important
TL;DR: The Mann-Whitney test is used as an alternative to a t test when the data are not normally distributed and can detect differences in shape and spread as well as just differences in medians.
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The bootstrap: A technique for data-driven statistics. Using computer-intensive analyses to explore experimental data
TL;DR: These techniques can supplement current nonparametric statistical methods and should be included, where appropriate, in the armamentarium of data processing methodologies.
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