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Relative Risk01:12

Relative Risk

191
Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
191
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

133
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
133
Design Example: Analyzing Capacity Contours for Flood Risk Assessment01:17

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

51
Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
51
Uncertainty: Overview00:59

Uncertainty: Overview

568
In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.
568
F Distribution01:19

F Distribution

3.7K
The F distribution was named after Sir Ronald Fisher, an English statistician. The F statistic is a ratio (a fraction) with two sets of degrees of freedom; one for the numerator and one for the denominator. The F distribution is derived from the Student's t distribution. The values of the F distribution are squares of the corresponding values of the t distribution. One-Way ANOVA expands the t test for comparing more than two groups. The scope of that derivation is beyond the level of this...
3.7K
Identifying Statistically Significant Differences: The F-Test01:14

Identifying Statistically Significant Differences: The F-Test

1.7K
The F-test is used to compare two sample variances to each other or compare the sample variance to the population variance. It is used to decide whether an indeterminate error can explain the difference in their values. The underlying assumptions that allow the use of the F-test include the data set or sets are normally distributed, and the data sets are independent of each other. The test statistic F is calculated by dividing one variance by another. In other words, the square of one standard...
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Related Experiment Video

Updated: Jul 12, 2025

Employing the Forced Oscillation Technique for the Assessment of Respiratory Mechanics in Adults
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Understanding risk with FOTRES?

Tim Räz1

  • 1Institute of Philosophy, University of Bern, Länggassstrasse 49a, 3012 Bern, Switzerland.

AI and Ethics
|November 2, 2023
PubMed
Summary
This summary is machine-generated.

The FOTRES recidivism risk assessment tool shows inadequate understanding of risk and fairness issues. Compared to COMPAS, FOTRES performs poorly on several criteria, with both tools lacking satisfactory performance overall.

Keywords:
COMPASFOTRESFairnessyMachine learningRecidivism risk assessmentUnderstanding

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Area of Science:

  • Criminology
  • Forensic Psychology
  • Legal Technology

Background:

  • Recidivism risk assessment instruments are crucial in criminal justice.
  • FOTRES and COMPAS are prominent tools used for predicting reoffending.
  • Evaluating the accuracy, validity, and fairness of these instruments is essential.

Purpose of the Study:

  • To critically evaluate the FOTRES recidivism risk assessment instrument.
  • To assess FOTRES's adequacy in understanding risk and its fairness.
  • To compare FOTRES's performance against the COMPAS instrument.

Main Methods:

  • Evaluation of FOTRES using criteria: empirical accuracy, representational accuracy, domain of validity, intelligibility, and fairness.
  • Comparative analysis between FOTRES and COMPAS.
  • Qualitative and quantitative assessment of instrument performance.

Main Results:

  • FOTRES demonstrates poor performance compared to COMPAS on specific evaluation criteria.
  • Both FOTRES and COMPAS exhibit unsatisfactory performance regarding certain key criteria.
  • Concerns identified regarding the intelligibility and fairness of both risk assessment tools.

Conclusions:

  • FOTRES requires significant improvement to meet standards of accuracy and fairness.
  • The study highlights limitations in current risk assessment technologies, including COMPAS.
  • Further research is needed to develop more reliable and equitable recidivism prediction tools.