Productive and perceptual constraints on speech-error correction

T Berg1

  • 1University of Oldenburg, Federal Republic of Germany.

Psychological Research
|January 1, 1992
PubMed

Related Concept Videos

Random and Systematic Errors01:20

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...
Barriers to Effective Communication I01:30

Barriers to Effective Communication I

A communication barrier is any distortion or interruption during a conversation, resulting in miscommunication of the message. A good communicator should know these barriers and continuously check for the listener's understanding by obtaining feedback.
Communication barriers include the following:
Physiological barriers: They are limitations caused by a person's health condition or disability, such as hearing loss, poor eyesight, illness, or unconsciousness. An example to overcome this barrier...
Types of Errors: Detection and Minimization01:12

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...
Detection of Gross Error: The Q Test01:00

Detection of Gross Error: The Q Test

When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...