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Related Concept Videos

Randomized Experiments01:13

Randomized Experiments

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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
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Bias01:22

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Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
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Random Variables01:09

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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.
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Understanding Deception01:14

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Deception is a pervasive aspect of human communication. Empirical studies have shown that most individuals engage in some form of deceit on a daily basis, with approximately 20% of social exchanges involving deceptive elements. Lying follows a developmental trajectory, peaking during adolescence and declining with age, possibly due to the maturation of cognitive control and social accountability.Cognitive and Social Factors in Deception DetectionDespite its prevalence, accurately detecting...
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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...
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Random and Systematic Errors01:20

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The Modified Temptation Resistance Task: A Paradigm to Elicit Children's Strategic Lie-telling
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Replicate and randomize, or lie.

R Webster1

  • 1Rothamsted Research, Harpenden, AL5 2JQ, UK.

Environmental Microbiology
|September 30, 2016
PubMed
Summary
This summary is machine-generated.

Biological populations exhibit natural variability. Replication and randomization are essential scientific methods for unbiased estimation of population characteristics and confidence intervals.

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Area of Science:

  • Biological sciences
  • Statistical inference

Background:

  • Biological populations inherently display variability.
  • Accurate estimation of population characteristics is crucial for scientific understanding.

Purpose of the Study:

  • To emphasize the necessity of replication and randomization in biological research.
  • To highlight the role of these methods in achieving unbiased and confident estimations.

Main Methods:

  • Replication of observations to estimate population characteristics.
  • Randomization of selection for unbiased data collection.

Main Results:

  • Replication allows for the estimation of population parameters.
  • Randomization ensures that estimates are free from systematic bias.
  • Combined, these methods provide statistically sound conclusions.

Conclusions:

  • Both replication and randomization are indispensable components of rigorous biological research.
  • Implementing these techniques is vital for generating reliable scientific data and inferences.