Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Probability in Statistics

Probability in Statistics

Probability is the likelihood of an event occurring. The term event is defined as a collection of results of a procedure. An event is a simple event when an outcome cannot be divided into simpler parts.
An example of a simple event is a coin toss. The result of a coin toss is either a head or a tail. Here, head and tail are two simple events. These two simple events make up the sample space. Further, the probability of an event occurring falls within the range of 0 to 1. The probability of an...

Binomial Probability Distribution

Binomial Probability Distribution

A binomial distribution is a probability distribution for a procedure with a fixed number of trials, where each trial can have only two outcomes.
The outcomes of a binomial experiment fit a binomial probability distribution. A statistical experiment can be classified as a binomial experiment if the following conditions are met:
There are a fixed number of trials. Think of trials as repetitions of an experiment. The letter n denotes the number of trials.
There are only two possible outcomes,...

Probability Distributions

Probability Distributions

The probability of a random variable x is the likelihood of its occurrence. A probability distribution represents the probabilities of a random variable using a formula, graph, or table. There are two types of probability distribution– discrete probability distribution and continuous probability distribution.
A discrete probability distribution is a probability distribution of discrete random variables. It can be categorized into binomial probability distribution and Poisson probability...

Statistical Analysis: Overview

Statistical Analysis: Overview

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...

Probability Laws

Probability Laws

Probability Histograms

Probability Histograms

A probability histogram is a visual representation of a probability distribution. Similar a typical histogram, the probability histogram consists of contiguous (adjoining) boxes. It has both a horizontal axis and a vertical axis. The horizontal axis is labeled with what the data represents. The vertical axis is labeled with probability. Each rectangular bar in the histogram is 1 unit wide, which suggests that the area under each bar equals the probability, P(x), where x is 1, 2, 3, and so on.

You might also read

Related Articles

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

Sort by

Same author

Using the R Package, <i>nsink,</i> to assess landscape N removal in coastal catchments.

F1000Research·2024

Same author

Shifting institutional culture to develop climate solutions with Open Science.

Ecology and evolution·2024

Same author

nsink: An R package for flow path nitrogen removal estimation.

Journal of open source software·2022

Same author

Beyond Old Pipes and Ailing Budgets: Systems Thinking on Twenty-First Century Water Infrastructure in Chicago.

Frontiers in built environment·2021

Same author

Rethinking the lake trophic state index.

PeerJ·2019

Same author

Performance of National Maps of Watershed Integrity at Watershed Scales.

Water·2018

Same journal

Assessing the performance of aged field-scale woodchip bioreactors in Iowa.

Journal of environmental quality·2026

Same journal

Spatial structuring dominates over seasonality in tropical coastal microbiomes: Insights from New Caledonia's Indo-Pacific lagoon.

Journal of environmental quality·2026

Same journal

Neonicotinoid contamination in aquatic ecosystems: A comprehensive review of toxic effects, underlying mechanisms, and mitigation strategies with implications for farmed teleosts.

Journal of environmental quality·2026

Same journal

Macroaggregates dominate colloidal phosphorus sequestration in Ultisol paddies: Evidence from size-fractionation experiments.

Journal of environmental quality·2026

Same journal

Harnessing biochar and plant growth-promoting bacteria for sustainable crop production under reclaimed water irrigation: A review.

Journal of environmental quality·2026

Same journal

Invasive plant species for compost production: Review of environmental and economic insights.

Journal of environmental quality·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 28, 2026

CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data

CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data

Published on: November 10, 2023

CProb: a computational tool for conducting conditional probability analysis.

Jeffrey W Hollister¹, Henry A Walker, John F Paul

¹U.S. Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research Lab., Atlantic Ecology Div., 27 Tarzwell Drive, Narragansett, RI 02882, USA. Hollister.jeff@epa.gov

Journal of Environmental Quality

|October 25, 2008

Summary

This summary is machine-generated.

Conditional probability analysis (CPA) assesses environmental contaminant impacts. A new Excel Add-in, CProb, simplifies CPA calculations and visualization for ecological condition assessments.

More Related Videos

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

Related Experiment Videos

Last Updated: Jun 28, 2026

CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data

CorrelationCalculator and Filigree: Tools for Data-Driven Network Analysis of Metabolomics Data

Published on: November 10, 2023

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

Published on: July 29, 2022

Area of Science:

Environmental Science
Ecology
Statistical Modeling

Background:

Conditional probability is key to understanding relationships between environmental stressors and ecological responses.
Existing methods for conditional probability analysis (CPA) often involve complex scripts or cumbersome spreadsheets.
There is a need for accessible tools to apply CPA for evaluating ecological conditions and setting environmental criteria.

Purpose of the Study:

To develop a user-friendly software application for performing conditional probability analysis.
To integrate CPA into a familiar interface, Microsoft Excel, enhancing accessibility and transparency.
To provide a tool for assessing associations between environmental contaminants and ecological conditions.

Main Methods:

Developed CProb, a Microsoft Excel Add-in utilizing R, R(D)com Server, and Visual Basic for Applications.
Implemented functionalities for calculating and plotting scatterplots, empirical cumulative distribution functions, and conditional probabilities.
Demonstrated the software's application using water quality and landscape examples.

Main Results:

CProb provides a transparent and accessible platform for conducting conditional probability analysis within Excel.
The software facilitates the visualization and calculation of key statistical measures relevant to environmental assessment.
Successful application illustrated through practical environmental case studies.

Conclusions:

The CProb Add-in simplifies complex statistical analyses for environmental data interpretation.
This tool enhances the evaluation of ecological conditions and supports the definition of environmental quality standards.
CProb offers a valuable, freely available resource for researchers and environmental managers.