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Related Concept Videos

Random Error01:04

Random Error

Random or indeterminate errors originate from various uncontrollable variables, such as variations in environmental conditions, instrument imperfections, or the inherent variability of the phenomena being measured. Usually, these errors cannot be predicted, estimated, or characterized because their direction and magnitude often vary in magnitude and direction even during consecutive measurements. As a result, they are difficult to eliminate. However, the aggregate effect of these errors can be...
Randomized Experiments01:13

Randomized Experiments

The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
Random Variables01:09

Random Variables

A random variable is a single numerical value that indicates the outcome of a procedure. The concept of random variables is fundamental to the probability theory and was introduced by a Russian mathematician, Pafnuty Chebyshev, in the mid-nineteenth century.
Uppercase letters such as X or Y denote a random variable. Lowercase letters like x or y denote the value of a random variable. If X is a random variable, then X is written in words, and x is given as a number.
For example, let X = the...
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...
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...
Random Sampling Method01:09

Random Sampling Method

Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...

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Related Experiment Video

Updated: May 10, 2026

Radio Frequency Identification and Motion-sensitive Video Efficiently Automate Recording of Unrewarded Choice Behavior by Bumblebees
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Radio Frequency Identification and Motion-sensitive Video Efficiently Automate Recording of Unrewarded Choice Behavior by Bumblebees

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[Non-random randomness].

Bertrand Jordan1

  • 1CoReBio PACA, case 901, parc scientifique de Luminy, 13288 Marseille Cedex 9, France. bertrand.jordan@univ-amu.fr

Medecine Sciences : M/S
|June 5, 2013
PubMed
Summary
This summary is machine-generated.

Whole-genome sequencing of identical twins and their parents reveals surprising new data on the rate and patterns of de novo mutations. This genetic analysis offers fresh perspectives on mutation accumulation in humans.

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Generating Strictly Controlled Stimuli for Figure Recognition Experiments
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Last Updated: May 10, 2026

Radio Frequency Identification and Motion-sensitive Video Efficiently Automate Recording of Unrewarded Choice Behavior by Bumblebees
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Published on: November 15, 2014

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Generating Strictly Controlled Stimuli for Figure Recognition Experiments

Published on: March 18, 2019

Area of Science:

  • Genetics
  • Genomics
  • Molecular Biology

Context:

  • Utilizing whole-genome sequencing technology.
  • Analyzing genetic data from monozygotic (identical) twin pairs and their parents.
  • Investigating the inheritance and occurrence of genetic variations.

Purpose:

  • To gain novel insights into the rate of de novo mutations.
  • To understand the distribution patterns of de novo mutations across the genome.
  • To explore the genetic contributions within families.

Summary:

  • Whole-genome sequencing was performed on monozygotic twin pairs and their parental generation.
  • The study provides surprising findings regarding the frequency and genomic locations of de novo mutations.
  • Analysis reveals new information about the dynamics of spontaneous genetic changes.

Impact:

  • Advances understanding of human genetic variation.
  • Informs studies on developmental biology and disease inheritance.
  • Provides a foundation for future research into mutation mechanisms.