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Hazard Rate

Hazard Rate

The hazard rate, also known as the hazard function or failure rate, is a statistical measure used to describe the instantaneous rate at which an event occurs, given that the event has not yet happened. From a probabilistic perspective, it represents the likelihood that a subject will experience the event in a very small time interval, conditional on surviving up to the beginning of that interval. In terms of frequency, the hazard rate can be viewed as the ratio of the number of events to the...

Types of Errors: Detection and Minimization

Types of Errors: Detection and Minimization

Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
Absolute error in a measurement is the numerical difference from the true or central value. Relative error is the ratio between absolute error and the true or central value, expressed as a percentage.
Errors can be classified by source, magnitude, and sign. There are three types of errors: systematic, random, and gross.
Systematic or...

Systematic Error: Methodological and Sampling Errors

Systematic Error: Methodological and Sampling Errors

In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
Sampling errors originate from improper sampling methods or the wrong sample population. These errors can be minimized by refining the sampling strategy. Defective instruments or faulty calibrations are the sources of instrumental...

Accuracy and Errors in Hypothesis Testing

Accuracy and Errors in Hypothesis Testing

Hypothesis testing is a fundamental statistical tool that begins with the assumption that the null hypothesis H0 is true. During this process, two types of errors can occur: Type I and Type II. A Type I error refers to the incorrect rejection of a true null hypothesis, while a Type II error involves the failure to reject a false null hypothesis.
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Random and Systematic Errors

Random and Systematic Errors

Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...

Random and Systematic Errors

Random and Systematic Errors

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Related Experiment Video

Updated: Apr 17, 2026

Errors as a Means of Reducing Impulsive Food Choice

Errors as a Means of Reducing Impulsive Food Choice

Published on: June 5, 2016

Information System Hazard Analysis: A Method for Identifying Technology-induced Latent Errors for Safety.

Jens H Weber¹, Fieran Mason-Blakley¹, Morgan Price²

¹Department of Computer Science, UVic, Victoria, Canada.

Studies in Health Technology and Informatics

|February 14, 2015

Summary

This summary is machine-generated.

Health information technology (HIT) systems frequently cause adverse events, yet safety improvements remain minimal. This study introduces Information System Hazard Analysis (ISHA), a proactive method to engineer safer health ICT systems by design.

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Last Updated: Apr 17, 2026

Errors as a Means of Reducing Impulsive Food Choice

Errors as a Means of Reducing Impulsive Food Choice

Published on: June 5, 2016

Area of Science:

Health Informatics
Software Engineering
Patient Safety

Background:

Health information and communication technologies (ICT) are critical systems where technology-induced adverse events are frequently reported.
Despite ongoing concerns, recent data indicate a lack of significant safety improvements in health ICT systems.
The prevailing industry approach remains reactive ('break & patch'), with limited use of proactive, systematic hazard analysis for 'safe by design' engineering.

Purpose of the Study:

To address the persistent safety issues in health ICT.
To introduce and describe a proactive hazard analysis method for engineering safer health ICT systems.
To promote the adoption of 'safe by design' principles in health technology development.

Main Methods:

Application of the Information System Hazard Analysis (ISHA) method.
ISHA adapts and integrates hazard analysis techniques from other safety-critical domains.
Customization of these techniques specifically for the complexities of ICT systems.

Main Results:

Demonstration of the ISHA methodology for proactive hazard identification in health ICT.
Provides a structured approach to systematically analyze potential hazards in health information systems.
Highlights the feasibility of applying advanced hazard analysis to improve ICT safety.

Conclusions:

The reactive 'break & patch' model is insufficient for ensuring health ICT safety.
Proactive methods like ISHA are essential for developing 'safe by design' health ICT.
Implementing ISHA can lead to more robust and safer health information systems, reducing adverse events.