Estimating the Correlation Coefficient: The Bootstrap Approach
Efron's bootstrap is a recently developed approach to nonparametric statistics, resampling from a set of observations to establish a basis for inference which is neither burdened with tenuous assumptions nor nonresponsive to distributional information carried by the data. In this article, the b...
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Veröffentlicht in: | Psychological bulletin 1985-07, Vol.98 (1), p.209-215 |
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container_title | Psychological bulletin |
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creator | Lunneborg, Clifford E |
description | Efron's bootstrap is a
recently developed approach to nonparametric statistics, resampling from a set of
observations to establish a basis for inference which is neither burdened with tenuous
assumptions nor nonresponsive to distributional information carried by the data. In this
article, the bootstrap approach is illustrated by developing nonparametric confidence
intervals for the Pearson product-moment correlation. The technique is shown to
be well within the capabilities of widely available eight-bit microcomputers. |
doi_str_mv | 10.1037/0033-2909.98.1.209 |
format | Article |
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observations to establish a basis for inference which is neither burdened with tenuous
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article, the bootstrap approach is illustrated by developing nonparametric confidence
intervals for the Pearson product-moment correlation. The technique is shown to
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recently developed approach to nonparametric statistics, resampling from a set of
observations to establish a basis for inference which is neither burdened with tenuous
assumptions nor nonresponsive to distributional information carried by the data. In this
article, the bootstrap approach is illustrated by developing nonparametric confidence
intervals for the Pearson product-moment correlation. The technique is shown to
be well within the capabilities of widely available eight-bit microcomputers.</description><subject>Biological and medical sciences</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Human</subject><subject>Nonparametric Statistical Tests</subject><subject>Psychology. Psychoanalysis. Psychiatry</subject><subject>Psychology. Psychophysiology</subject><subject>Psychometrics. Statistics. Methodology</subject><subject>Statistical Correlation</subject><subject>Statistics. 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observations to establish a basis for inference which is neither burdened with tenuous
assumptions nor nonresponsive to distributional information carried by the data. In this
article, the bootstrap approach is illustrated by developing nonparametric confidence
intervals for the Pearson product-moment correlation. The technique is shown to
be well within the capabilities of widely available eight-bit microcomputers.</abstract><cop>Washington, DC</cop><pub>American Psychological Association</pub><doi>10.1037/0033-2909.98.1.209</doi><tpages>7</tpages></addata></record> |
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issn | 0033-2909 1939-1455 |
language | eng |
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source | Periodicals Index Online; APA PsycARTICLES |
subjects | Biological and medical sciences Fundamental and applied biological sciences. Psychology Human Nonparametric Statistical Tests Psychology. Psychoanalysis. Psychiatry Psychology. Psychophysiology Psychometrics. Statistics. Methodology Statistical Correlation Statistics. Mathematics |
title | Estimating the Correlation Coefficient: The Bootstrap Approach |
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