Bootstrapped confidence intervals as an approach to statistical inference

Research output: Contribution to journalArticlepeer-review

Abstract

Confidence intervals are in many ways a more satisfactory basis for statistical inference than hypothesis tests. This paper explains a simple method for using bootstrap resampling to derive confidence intervals. This method can be used for a wide variety of statistics - including the mean and median, the difference of two means or proportions, and correlation and regression coefficients. It can be implemented by an Excel spreadsheet, which is available to readers on the web. The rationale behind the method is transparent, and it relies on almost no sophisticated statistical concepts.
Original languageEnglish
Pages (from-to)454-470
Number of pages17
JournalOrganizational Research Methods
Volume8
Issue number4
DOIs
Publication statusPublished - Oct 2005

Fingerprint

Dive into the research topics of 'Bootstrapped confidence intervals as an approach to statistical inference'. Together they form a unique fingerprint.

Cite this