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→Non-parametric and Bootstrapping methods
[[Non-parametric statistics]] are any one of many methods that attempt to define descriptive characteristics or make inferential claims with out the need of tightly confined parameters. The main goals is to try and eliminate the need for assumptions without sacrificing power and accuracy.
[[Non-parametric statistics]] are any one of many methods that attempt to define descriptive characteristics or make inferential claims with out the need of tightly confined parameters. The main goals is to try and eliminate the need for assumptions without sacrificing power and accuracy.
[[Bootstrapping statistics]] is a particularly popular non-parametric approach. Bootstrapping is computationally costly and has only recently become feasible for most data sets. It involves [sampling with replacement]] from the given data set perhaps as many as 100,000 times in order to determine mean, error, best fits and comparisons of data sets.
[[Bootstrapping statistics]] is a particularly popular non-parametric approach. Bootstrapping is computationally costly and has only recently become feasible for most data sets. It involves [[sampling with replacement]] from the given data set perhaps as many as 100,000 times in order to determine mean, error, best fits and comparisons of data sets.
==References==
==References==