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

Statistical Analysis: Overview01:11

Statistical Analysis: Overview

14.4K
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...
14.4K
Statgraphics01:10

Statgraphics

483
Statgraphics is a comprehensive statistical software suite designed for both basic and advanced data analysis. Originating in 1980 at Princeton University under Dr. Neil W. Polhemus, it was one of the pioneering tools for statistical computing on personal computers, with its public release in 1982 marking an early milestone in data science software. Over the years, it has evolved into a robust platform for data science, offering tools for regression analysis, ANOVA, multivariate statistics,...
483
Statistical Significance01:37

Statistical Significance

20.9K
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...
20.9K
Statistical Hypothesis Testing01:16

Statistical Hypothesis Testing

6.0K
Hypothesis testing is a critical statistical procedure facilitating informed, evidence-based decisions. It begins with a hypothesis, which is a tentative explanation, or a prediction about a population parameter. This hypothesis can be either a null hypothesis (H0), indicating no effect or difference, or an alternative hypothesis (Ha), suggesting an effect or difference.
Statistical significance measures the probability that an observed result occurred by chance. If this probability, known as...
6.0K
Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data01:16

Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data

720
Statistical inference techniques, paramount in hypothesis testing, differentiate into two broad categories: parametric and nonparametric statistics.
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance,...
720
Statistical Methods to Analyze Parametric Data: ANOVA01:12

Statistical Methods to Analyze Parametric Data: ANOVA

2.2K
Analysis of Variance, or ANOVA, is a powerful statistical technique used to analyze parametric data, primarily in research and experimental studies. It's designed to compare the means of two or more groups, assisting researchers in identifying any significant differences between these group means. There are two main types of ANOVA based on the complexity of the analysis: one-way and two-way.
One-way ANOVA is applied when a single independent variable or factor is scrutinized. It compares...
2.2K

You might also read

Related Articles

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

Sort by
Same author

Estimating mercury exposure in amphibians using non-lethal tissue sampling.

Ecotoxicology (London, England)·2026
Same author

Fomites Could Determine Severity of SARS-CoV-2 Outbreaks in Low-Density White-Tailed Deer (<i>Odocoileus virginianus</i>) Populations.

Transboundary and emerging diseases·2025
Same author

Independent and interactive effects of disease and methylmercury on demographic rates across multiple amphibian populations.

Scientific reports·2025
Same author

Reducing uncertainty with iterative model updating parses effects of competition and environment on salamander occupancy.

Oecologia·2024
Same author

One Health collaboration is more effective than single-sector actions at mitigating SARS-CoV-2 in deer.

Nature communications·2024
Same author

Corrigendum to 'Evaluating the effect of expert elicitation techniques on population status assessment in the face of large uncertainty' [J. Environ. Manag. 306 (2022) /114453].

Journal of environmental management·2024

Related Experiment Video

Updated: Apr 26, 2026

Systematic Assessment of Mammalian Skull Specimens for Dental and Temporomandibular Joint Pathology
07:26

Systematic Assessment of Mammalian Skull Specimens for Dental and Temporomandibular Joint Pathology

Published on: August 22, 2022

1.7K

Please don't misuse the museum: 'declines' may be statistical.

Evan H Campbell Grant1

  • 1USGS-Patuxent Wildlife Research Center, S.O. Conte Anadromous Fish Research Center, 1 Migratory Way, Turners Falls, MA, 01376, USA.

Global Change Biology
|August 8, 2014
PubMed
Summary
This summary is machine-generated.

Museum records offer valuable long-term population data. However, apparent declines may stem from sampling biases, not just real population changes, necessitating careful statistical evaluation.

Keywords:
availabilitydeclinesdetection probabilityhistoric resurveysmuseum datashrinking salamanderstemporary emigration

More Related Videos

Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images SDM-PSI
06:26

Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images SDM-PSI

Published on: November 27, 2019

82.4K
Highlighting and Reducing the Impact of Negative Aging Stereotypes During Older Adults' Cognitive Testing
06:58

Highlighting and Reducing the Impact of Negative Aging Stereotypes During Older Adults' Cognitive Testing

Published on: January 24, 2020

6.3K

Related Experiment Videos

Last Updated: Apr 26, 2026

Systematic Assessment of Mammalian Skull Specimens for Dental and Temporomandibular Joint Pathology
07:26

Systematic Assessment of Mammalian Skull Specimens for Dental and Temporomandibular Joint Pathology

Published on: August 22, 2022

1.7K
Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images SDM-PSI
06:26

Meta-analysis of Voxel-Based Neuroimaging Studies using Seed-based d Mapping with Permutation of Subject Images SDM-PSI

Published on: November 27, 2019

82.4K
Highlighting and Reducing the Impact of Negative Aging Stereotypes During Older Adults' Cognitive Testing
06:58

Highlighting and Reducing the Impact of Negative Aging Stereotypes During Older Adults' Cognitive Testing

Published on: January 24, 2020

6.3K

Area of Science:

  • Ecology
  • Conservation Biology
  • Museum Science

Background:

  • Long-term population data are crucial for conservation but often scarce.
  • Museum records provide extensive historical data across broad spatial scales.
  • Distinguishing real population changes from observational biases is a significant challenge.

Purpose of the Study:

  • To highlight the utility of museum records for assessing population status.
  • To address statistical challenges in interpreting historical population data.
  • To emphasize the need for rigorous statistical evaluation when using museum collections.

Main Methods:

  • Review of statistical considerations for utilizing museum records.
  • Discussion of potential biases in historical data collection.
  • Exploration of environmental covariates influencing both population presence and detectability.

Main Results:

  • Museum records can offer insights into population trends over decades.
  • Changes in detectability, influenced by environmental factors, can mimic population declines.
  • Proper statistical methods are essential to avoid misinterpreting data.

Conclusions:

  • Museum collections are a valuable resource for ecological studies.
  • Careful statistical analysis is required to account for biases in historical data.
  • Understanding detectability issues is key to accurate population trend assessment.