Cheating 2.0: A reprofiling of the 10 most wanted test cheaters in the digital age

  • 0University College London School of Life and Medical Sciences, London, UK.

|

|

Summary

This summary is machine-generated.

This study is currently under embargo and was published in Early View by mistake. It will be officially republished in December 2025 for wider access.

Area Of Science

  • Not specified in the provided abstract.

Background

  • Not specified in the provided abstract.

Purpose Of The Study

  • Not specified in the provided abstract.

Main Methods

  • Not specified in the provided abstract.

Main Results

  • Not specified in the provided abstract.

Conclusions

  • Not specified in the provided abstract.

Related Concept Videos

Bullying 02:04

8.3K

A modern form of aggression is bullying. As you learn in your study of child development, socializing and playing with other children is beneficial for children’s psychological development. However, as you may have experienced as a child, not all play behavior has positive outcomes. Some children are aggressive and want to play roughly. Other children are selfish and do not want to share toys. One form of negative social interactions among children that has become a national concern is...

Reliability and Validity 01:29

12.6K

Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.

Unfortunately, being consistent in measurement does not necessarily mean that you have measured something correctly. To illustrate this concept, consider a kitchen...

Detection of Gross Error: The <em>Q</em> Test 01:00

5.0K

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...

Significance Testing: Overview 01:04

3.3K

Significance testing is a set of statistical methods used to test whether a claim about a parameter is valid. In analytical chemistry, significance testing is used primarily to determine whether the difference between two values comes from determinate or random errors. The effect of a particular change in the measurement protocol, analyst, or sample itself can cause a deviation from the expected result. In the case of a suspected deviation/outlier, we need to be able to confirm mathematically...

Steps in Outbreak Investigation 01:18

101

In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:

Predicting Outbreaks
Predictive analytics, a branch of statistics, uses historical data, algorithmic models, and...

Quantifying and Rejecting Outliers: The Grubbs Test 01:02

1.4K

Sometimes, a data set can have a recorded numerical observation that greatly  deviates from the rest of the data. Assuming that the data is normally distributed, a statistical method called the Grubbs test can be used to determine whether the observation is truly an outlier.  To perform a two-tailed Grubbs test, first, calculate the absolute difference between the outlier and the mean. Then, calculate the ratio between this difference and the standard deviation of the sample. This...