Inferring uncertainty from interval estimates: Effects of alpha level and numeracy

Luke F. Rinne, Michèle M.M. Mazzocco

Research output: Contribution to journalArticlepeer-review

Abstract

Interval estimates are commonly used to descriptively communicate the degree of uncertainty in numerical values. Conventionally, low alpha levels (e.g.,.05) ensure a high probability of capturing the target value between interval endpoints. Here, we test whether alpha levels and individual differences in numeracy influence distributional inferences. In the reported experiment, participants received prediction intervals for fictitious towns' annual rainfall totals (assuming approximately normal distributions). Then, participants estimated probabilities that future totals would be captured within varying margins about the mean, indicating the approximate shapes of their inferred probability distributions. Results showed that low alpha levels (vs. moderate levels; e.g.,.25) more frequently led to inferences of over-dispersed approximately normal distributions or approximately uniform distributions, reducing estimate accuracy. Highly numerate participants made more accurate estimates overall, but were more prone to inferring approximately uniform distributions. These findings have important implications for presenting interval estimates to various audiences.

Original languageEnglish (US)
Pages (from-to)330-344
Number of pages15
JournalJudgment and Decision Making
Volume8
Issue number3
StatePublished - May 2013

Keywords

  • Decision-making
  • Interval estimates
  • Numeracy
  • Numerical cognition
  • Probability judgment

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Applied Psychology
  • Economics and Econometrics

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