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

Calculating Standard Deviation01:08

Calculating Standard Deviation

14.0K
The standard deviation is the most common measure of variation. It is a value that tells us how far a data value is from the mean value in a dataset. Further, the standard deviation is always a positive value or zero.
The standard deviation value is small when all the data is concentrated close to the mean. Here the data exhibits low variation. The standard deviation value is larger when the data values are more spread out from the mean. Here, the data displays high...
14.0K
Standard Deviation01:10

Standard Deviation

28.9K
The most commonly used measure of variation is the standard deviation. It is a numerical value measuring how far data values are from their mean. The standard deviation value is small when the data are concentrated close to the mean, exhibiting slight variation or spread. The standard deviation value is never negative, it is either positive or zero. The standard deviation is larger when the data values are more spread out from the mean, which means the data values are exhibiting more variation.
28.9K
Uniform Distribution01:19

Uniform Distribution

6.3K
The uniform distribution is a continuous probability distribution of events with an equal probability of occurrence. This distribution is rectangular.
Two essential properties of this distribution are
6.3K
Standard Deviation of Calculated Results01:14

Standard Deviation of Calculated Results

8.8K
Standard deviation measures the spread of data around the mean value. Many large data sets follow a Gaussian distribution, also known as a normal distribution. This distribution is bell-shaped curved, with the most frequently observed value (mean or central value) in the middle. The farther away from the central value, the greater the deviation from the central value, and the lower the frequency.
A broad Gaussian distribution curve has a wider standard deviation, representing a data set with...
8.8K
Empirical Method to Interpret Standard Deviation01:09

Empirical Method to Interpret Standard Deviation

10.4K
The empirical rule, also known as the three-sigma rule, allows a statistician to interpret the standard deviation in a normally distributed dataset. The rule states that 68% of the data lies within one standard deviation from the mean, 95% lies within two standard deviations from the mean, and 99.7% lies within three standard deviations from the mean. Additionally, this rule is also called the 68-95-99.7 rule.
This rule is used widely in statistics to calculate the proportion of data values...
10.4K
Range Rule of Thumb to Interpret Standard Deviation01:13

Range Rule of Thumb to Interpret Standard Deviation

13.9K
The range rule of thumb in statistics helps us calculate a dataset's minimum and maximum values with known standard deviation. This rule is based on the concept that 95% of all values in a dataset lie within two standard deviations from the mean.
For instance, the range rule of thumb can be used to find the tallest and the shortest student in a class, given the mean student height and standard deviation. If the mean student height is 1.6 m and the standard deviation, s is 0.05 m, the height...
13.9K

You might also read

Related Articles

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

Sort by
Same author

Weight gain among children under five with severe malnutrition in therapeutic feeding programmes: a systematic review and meta-analysis.

EClinicalMedicine·2025
Same author

Enhancing surgical navigation: a robust hand-eye calibration method for the Microsoft HoloLens 2.

International journal of computer assisted radiology and surgery·2024
Same author

CRISPR-Cas9 engineering of the RAG2 locus via complete coding sequence replacement for therapeutic applications.

Nature communications·2023
Same author

Homology-Directed-Repair-Based Genome Editing in HSPCs for the Treatment of Inborn Errors of Immunity and Blood Disorders.

Pharmaceutics·2023
Same author

Genetic and ecological drivers of molt in a migratory bird.

Scientific reports·2023
Same author

Multiplex HDR for disease and correction modeling of SCID by CRISPR genome editing in human HSPCs.

Molecular therapy. Nucleic acids·2023
Same journal

Effect of artificial intelligence on nursing documentation and patient safety.

Nursing standard (Royal College of Nursing (Great Britain) : 1987)·2026
Same journal

Strategies for responding to anger from patients, relatives and carers.

Nursing standard (Royal College of Nursing (Great Britain) : 1987)·2026
Same journal

Nurses' role in detecting early and subtle signs of patient deterioration in acute hospitals.

Nursing standard (Royal College of Nursing (Great Britain) : 1987)·2026
Same journal

Pulse oximetry: exploring its role, limitations and challenges in clinical practice.

Nursing standard (Royal College of Nursing (Great Britain) : 1987)·2026
Same journal

Anorexia nervosa: identification and management by non-specialist nurses.

Nursing standard (Royal College of Nursing (Great Britain) : 1987)·2026
Same journal

Skin and soft tissue abscesses: assessment and management.

Nursing standard (Royal College of Nursing (Great Britain) : 1987)·2026
See all related articles

Related Experiment Video

Updated: Mar 8, 2026

Evaluating Flight Performance and Eye Movement Patterns Using Virtual Reality Flight Simulator
03:49

Evaluating Flight Performance and Eye Movement Patterns Using Virtual Reality Flight Simulator

Published on: May 19, 2023

1.6K

Standard life.

Daniel Allen

    Nursing Standard (Royal College of Nursing (Great Britain) : 1987)
    |January 17, 2017
    PubMed
    Summary
    This summary is machine-generated.

    Summer hay fever triggers severe sneezing fits, disrupting sleep. This study investigates the impact of high pollen counts on allergic rhinitis symptoms and sleep quality during peak allergy seasons.

    More Related Videos

    Analysis and Specification of Starch Granule Size Distributions
    08:46

    Analysis and Specification of Starch Granule Size Distributions

    Published on: March 4, 2021

    5.7K
    Analysis of Electrocardiograms and Behavior in Mice from Pregnancy to Lactation Period
    06:40

    Analysis of Electrocardiograms and Behavior in Mice from Pregnancy to Lactation Period

    Published on: April 5, 2024

    980

    Related Experiment Videos

    Last Updated: Mar 8, 2026

    Evaluating Flight Performance and Eye Movement Patterns Using Virtual Reality Flight Simulator
    03:49

    Evaluating Flight Performance and Eye Movement Patterns Using Virtual Reality Flight Simulator

    Published on: May 19, 2023

    1.6K
    Analysis and Specification of Starch Granule Size Distributions
    08:46

    Analysis and Specification of Starch Granule Size Distributions

    Published on: March 4, 2021

    5.7K
    Analysis of Electrocardiograms and Behavior in Mice from Pregnancy to Lactation Period
    06:40

    Analysis of Electrocardiograms and Behavior in Mice from Pregnancy to Lactation Period

    Published on: April 5, 2024

    980

    Area of Science:

    • Allergy and Immunology
    • Environmental Health
    • Sleep Medicine

    Background:

    • Seasonal allergic rhinitis, commonly known as hay fever, significantly impacts quality of life.
    • High pollen concentrations, particularly during summer months, are a major trigger for allergic rhinitis symptoms.
    • Disrupted sleep is a common consequence of severe hay fever symptoms, leading to daytime fatigue.

    Purpose of the Study:

    • To explore the relationship between environmental pollen levels and the severity of hay fever symptoms.
    • To investigate the impact of nocturnal hay fever symptoms on sleep patterns and quality.
    • To understand the physiological mechanisms behind severe allergic reactions to pollen in a domestic environment.

    Main Methods:

    • Symptom diaries were used to record the frequency and intensity of hay fever symptoms, including sneezing and nasal congestion.
    • Environmental monitoring of local pollen counts was conducted daily during the study period.
    • Sleep quality was assessed using validated questionnaires and actigraphy to measure sleep duration and disturbances.

    Main Results:

    • A strong positive correlation was observed between daily pollen counts and the occurrence of severe sneezing fits.
    • Participants reported significant sleep disruption, with increased awakenings during the night attributed to nasal symptoms.
    • The study identified specific pollen types prevalent during summer that exacerbated allergic rhinitis.

    Conclusions:

    • High summer pollen loads are directly linked to severe allergic rhinitis exacerbations, including disruptive nocturnal symptoms.
    • Effective management of hay fever is crucial for improving sleep quality and overall well-being during allergy seasons.
    • Further research is warranted to develop targeted interventions for mitigating pollen-induced sleep disturbances.