Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Random Error01:04

Random Error

1.2K
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...
1.2K
Statistical Analysis: Overview01:11

Statistical Analysis: Overview

6.8K
When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
6.8K
Random and Systematic Errors01:20

Random and Systematic Errors

11.5K
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...
11.5K
Systematic Error: Methodological and Sampling Errors01:15

Systematic Error: Methodological and Sampling Errors

1.7K
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...
1.7K
Statistical Significance01:50

Statistical Significance

20.3K
Once data is collected from both the experimental and the control groups, a statistical analysis is conducted to find out if there are meaningful differences between the two groups. A statistical analysis determines how likely any difference found is due to chance (and thus not meaningful). In psychology, group differences are considered meaningful, or significant, if the odds that these differences occurred by chance alone are 5 percent or less. Stated another way, if we repeated this...
20.3K
Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

756
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
756

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Reply to the Comments on "Meta-analysis Framework as a Form of Original Research".

Indian journal of psychological medicine·2026
Same author

Oral Ketamine for Treatment-refractory Major Depressive Disorder and the Complicating Role of Concurrent Stressors: Implications for Research and Practice.

Indian journal of psychological medicine·2026
Same author

Meta-analysis Framework as a Form of Original Research.

Indian journal of psychological medicine·2025
Same author

Comments on "The Efficacy and Durability of Mindfulness-based Cognitive Therapy in the Treatment of Anxiety and Depressive Disorders: A Systematic Review and Meta-analysis".

Indian journal of psychological medicine·2025
Same author

Fixed Effect Versus Random Effects Models in Meta-analysis: As Simple as It Gets.

Indian journal of psychological medicine·2025
Same author

The Digital Personal Data Protection Act 2023: Implications for Mental Healthcare Practice in India.

Indian journal of psychological medicine·2025
Same journal

Narcissistic Abuse Cycle Deserves Clinical and Research Attention.

Indian journal of psychological medicine·2026
Same journal

Journal Instructions Are Not Optional: Yet Authors Still Ignore Them.

Indian journal of psychological medicine·2026
Same journal

Comments on "Psychometric Properties, Stability, and Predictive Validity of the Hindi Version of the Prolonged Grief Disorder Scale (PG-13-R-H) Among Hindi-speaking Adults in the United States".

Indian journal of psychological medicine·2026
Same journal

Urgent, Exceptional, and Above the Rules: Author Entitlement in Biomedical Publishing.

Indian journal of psychological medicine·2026
Same journal

Corrigendum: Responses to the Comments on "The Efficacy and Durability of Mindfulness-based Cognitive Therapy in the Treatment of Anxiety and Depressive Disorders: A Systematic Review and Meta-analysis."

Indian journal of psychological medicine·2026
Same journal

Integrating Lived Experience Perspectives in AI-based Mental Health Research: A Practice-based Reflective Account.

Indian journal of psychological medicine·2026
See all related articles

Related Experiment Video

Updated: Aug 10, 2025

Continuous Measurement of Biological Noise in Escherichia Coli Using Time-lapse Microscopy
08:25

Continuous Measurement of Biological Noise in Escherichia Coli Using Time-lapse Microscopy

Published on: April 27, 2021

3.8K

Understanding Statistical Noise in Research: 1. Basic Concepts.

Chittaranjan Andrade1

  • 1Dept. of Clinical Psychopharmacology and Neurotoxicology, National Institute of Mental Health and Neurosciences, Bangaluru, Karnataka 560029, India.

Indian Journal of Psychological Medicine
|February 13, 2023
PubMed
Summary
This summary is machine-generated.

Statistical noise, measured by standard deviation, distorts research signals from extraneous variables. This series explains these core concepts for clearer scientific understanding.

Keywords:
Signalmeannoisestandard deviationunknown confoundsunmeasured confounds

More Related Videos

Sealable Femtoliter Chamber Arrays for Cell-free Biology
13:44

Sealable Femtoliter Chamber Arrays for Cell-free Biology

Published on: March 11, 2015

9.6K
Author Spotlight: Using Hyperpolarized Xenon-129 MRI to Study Lung Diseases
09:55

Author Spotlight: Using Hyperpolarized Xenon-129 MRI to Study Lung Diseases

Published on: January 5, 2024

1.3K

Related Experiment Videos

Last Updated: Aug 10, 2025

Continuous Measurement of Biological Noise in Escherichia Coli Using Time-lapse Microscopy
08:25

Continuous Measurement of Biological Noise in Escherichia Coli Using Time-lapse Microscopy

Published on: April 27, 2021

3.8K
Sealable Femtoliter Chamber Arrays for Cell-free Biology
13:44

Sealable Femtoliter Chamber Arrays for Cell-free Biology

Published on: March 11, 2015

9.6K
Author Spotlight: Using Hyperpolarized Xenon-129 MRI to Study Lung Diseases
09:55

Author Spotlight: Using Hyperpolarized Xenon-129 MRI to Study Lung Diseases

Published on: January 5, 2024

1.3K

Area of Science:

  • Statistics in scientific research
  • Measurement and data analysis

Background:

  • Research signals represent outcomes or relationships between variables.
  • Statistical noise, arising from extraneous variables, obscures these signals.
  • Subject-to-subject variation in signals is quantified by standard deviation.

Purpose of the Study:

  • To define and explain the concepts of 'signal' and 'statistical noise' in research.
  • To elucidate the role of extraneous variables in generating statistical noise.
  • To establish standard deviation as a measure of statistical noise.

Main Methods:

  • Conceptual explanation of research signals and noise.
  • Illustrative examples to clarify abstract concepts.
  • Discussion of variable measurement (adequate, inadequate, unmeasured, unknown).

Main Results:

  • The standard deviation quantifies statistical noise.
  • Extraneous variables are the source of statistical noise.
  • Understanding signal and noise is crucial for accurate research interpretation.

Conclusions:

  • Standard deviation is a key metric for assessing the impact of statistical noise.
  • Accurate identification and management of extraneous variables are vital for signal integrity.
  • This foundational article sets the stage for advanced statistical concepts in research.