Titlebook: Applied Nonparametric Statistical Methods; Peter Sprent Book 1989 P. Sprent 1989 correlation.estimator.linear regression.median.random var

Contend

FUSC

https://doi.org/10.1007/978-3-662-41394-4cing quantitative results will be aware of more sophisticated statistical techniques, again many having parametric and nonparametric counterparts. In this chapter we look briefly at some more advanced nonparametric procedures — some recent. This is not a comprehensive review; that would need a furth

reflection

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PLE

Location estimates for single samples,hapters 2 and 3 are devoted to single samples. Most practical problems involve comparison of, or studying relations between, several samples, but many basic nonparametric notions are applicable also to a single sample and the logic behind them is easily explained in this basic situation.

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cumulative

Bivariate and multivariate data,sample of bivariate observations (., .), . = 1, 2,..., . that are at least ordinal. If they are measurements or counts we sometimes convert these to ranks and, in the case of correlation, base our statistics on these ranks. Depending on the precise problem, procedures for regression will sometimes use ranks and sometimes the original observations.

AIL

Looking ahead,cing quantitative results will be aware of more sophisticated statistical techniques, again many having parametric and nonparametric counterparts. In this chapter we look briefly at some more advanced nonparametric procedures — some recent. This is not a comprehensive review; that would need a further book.

canvass

CHOP

Entwicklung der chemischen KrystallographieIn most of this book we assume only a rudimentary knowledge of statistics like that provided by a service or introductory course of 10 to 20 lectures, or by reading a simple text like . (Rowntree, 1981).

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