Communicating Statistical Information

  title={Communicating Statistical Information},
  author={Ulrich Hoffrage and Samuel Lindsey and Ralph Hertwig and Gerd Gigerenzer},
  pages={2261 - 2262}
Most people, experts included, have difficulties understanding and combining statistical information effectively. Hoffrage et al. demonstrate that these difficulties can be considerably reduced by communicating the information in terms of natural frequencies rather than in terms of probabilities. Several applications in medicine, legal decision-making, and education are discussed. 
The Language of Conditional Probability
Statistical terms are accurate and powerful but can sometimes lead to misleading impressions among beginning students. Discrepancies between the popular and statistical meanings of “conditional” are
How to confuse with statistics or: the use and misuse of conditional probabilities
How consumers of statistical information may be confused when this information is presented in terms of conditional probabilities is shown and how either confusion or lies can be avoided by using alternative modes of conveying statistical information is suggested.
Edinburgh medical students 1872
absolute risk reduction). The wide scope for manipulating representations of statistical information is a challenge to the ideal of informed consent. 16 Where there is a risk of influencing outcomes
Communication of risks: an analysis beyond numbers.
  • A. Ghosh, K. Ghosh
  • Medicine
    QJM : monthly journal of the Association of Physicians
  • 2003
Sir, The recent commentary by Professor McManus1 provides an excellent overview of Dr Gigerenzer’s book, and summarizes the overwhelming appeal of ‘natural frequency’ over traditional descriptions
Communicating Quantitative Risk Information
This chapter reviews literature indicating that some representations and formats of quantitative risk information are easier to understand than others, and details the ways in which the message sender, a risk communicator, may hinder effective communication.
The Non-Use of Bayes Rule: Representative Evidence on Bounded Rationality
The results show that only a small fraction of the population responds consistently with Bayes'' rule, and that the probability to give normatively correctanswers decreases with the level of education.
Overcoming number numbness in prenatal risk communication
Efficient prenatal risk communication hinges upon parents' grasp of statistical information. When forming their subjective representation of a probability, pregnant women may focus on inappropriate
Natural frequencies improve Bayesian reasoning in simple and complex inference tasks
This work shows that natural frequencies facilitate Bayesian reasoning in a much broader class of situations than previously thought, and shows that teaching natural frequencies for simple tasks with one dichotomous cue and two hypotheses leads to a transfer of learning to complex tasks with three cue values and two cues.
To Bayes or Not to Bayes? A Comparison of Two Classes of Models of Information Aggregation
The DMs' aggregates were more in line with the naive Bayes rule when the advisors provided extreme forecasts were highly consistent with each other, and induced high levels of confidence, and their aggregateswere predicted well by a simple averaging rule.


How to Improve Bayesian Reasoning: Comment on Gigerenzer and Hoffrage (1995)
G. Gigerenzer and U. Hoffrage (1995) claimed that Bayesian inference problems, which have been notoriously difficult for laypeople to solve using base rates, hit rates, and false-alarm rates, become
Overcoming difficulties in Bayesian reasoning: A reply to Lewis and Keren (1999) and Mellers and McGraw (1999).
Results indicate that teaching frequency representations fosters insight into Bayesian reasoning in medical experts, and opens up applications in medicine, law, statistics education, and other fields.
Using natural frequencies to improve diagnostic inferences
Representing information in natural frequencies is a fast and effective way of facilitating diagnosis insight, which in turn helps physicians to better communicate risks to patients, and patients to better understand these risks.
Judgment under Uncertainty: Heuristics and Biases.
Three heuristics that are employed in making judgements under uncertainty are described: representativeness, availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development.
The Interdependence of Science and Law
The use of court-appointed scientific experts in technical cases to assist judges in gleaning unbiased information and determining the validity of scientific evidence is used.
How to Improve Bayesian Reasoning Without Instruction: Frequency Formats
By analyzing several thousand solutions to Bayesian problems, the authors found that when information was presented in frequency formats, statistically naive participants derived up to 50% of all inferences by Bayesian algorithms.
The base rate fallacy reconsidered: Descriptive, normative, and methodological challenges
  • J. Koehler
  • Psychology
    Behavioral and Brain Sciences
  • 1996
Abstract We have been oversold on the base rate fallacy in probabilistic judgment from an empirical, normative, and methodological standpoint. At the empirical level, a thorough examination of the
The Random Match Probability (RMP) in DNA Evidence: Irrelevant and Prejudicial?
It is shown that R MPs contribute little to an assessment of the diagnostic significance of a reported DNA match beyond that given by the false positive laboratory error rate when RMPs are several orders of magnitude smaller than this error rate.
Interpretation by physicians of clinical laboratory results.
A small survey was conducted to obtain some idea of how physicians do, in fact, interpret a laboratory result, and asked if a test to detect a disease whose prevalence is 1/1000 has a false positive rate of .
Error and Exaggeration in the Presentation of DNA Evidence at Trial
This Article identifies some of the subtle, but common, exaggerations that have occurred at trial, and classifies each in relation to the three questions that are suggested by the chain of reasoning