Related Experiment Video

Updated: Aug 2, 2026

Measuring Spatially- and Directionally-varying Light Scattering from Biological Material
11:57

Measuring Spatially- and Directionally-varying Light Scattering from Biological Material

Published on: May 20, 2013

Probability density cloud as a geometrical tool to describe statistics of scattered light

Natalia Yaitskova

    Journal of the Optical Society of America. A, Optics, Image Science, and Vision
    |April 5, 2017
    PubMed

    More Related Videos

    Controlled Synthesis and Fluorescence Tracking of Highly Uniform Poly(N-isopropylacrylamide) Microgels11:34

    Controlled Synthesis and Fluorescence Tracking of Highly Uniform Poly(N-isopropylacrylamide) Microgels

    Published on: September 8, 2016

    Scattering And Absorption of Light in Planetary Regoliths11:34

    Scattering And Absorption of Light in Planetary Regoliths

    Published on: July 1, 2019

    Related Concept Videos

    Probability Distributions01:32

    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...
    Probability Histograms01:17

    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.
    Poisson Probability Distribution01:09

    Poisson Probability Distribution

    A Poisson probability distribution is a discrete probability distribution. It gives the probability of a number of events occurring in a fixed interval of time or space if these events happen at a known average rate and independently of the time since the last event. For example, a book editor might be interested in the number of words spelled incorrectly in a particular book. It might be that, on average, there are five words spelled incorrectly in 100 pages. The interval is 100 pages.
    The...
    Gauss's Law01:07

    Gauss's Law

    If a closed surface does not have any charge inside where an electric field line can terminate, then the electric field line entering the surface at one point must necessarily exit at some other point of the surface. Therefore, if a closed surface does not have any charges inside the enclosed volume, then the electric flux through the surface is zero. What happens to the electric flux if there are some charges inside the enclosed volume? Gauss's law gives a quantitative answer to this question.
    Gauss's Law: Spherical Symmetry01:26

    Gauss's Law: Spherical Symmetry

    A charge distribution has spherical symmetry if the density of charge depends only on the distance from a point in space and not on the direction. In other words, if the system is rotated, it doesn't look different. For instance, if a sphere of radius R is uniformly charged with charge density ρ0, then the distribution has spherical symmetry. On the other hand, if a sphere of radius R is charged so that the top half of the sphere has a uniform charge density ρ1 and the bottom half has a uniform...
    Applications of Integration to Probability Density Functions01:27

    Applications of Integration to Probability Density Functions

    Continuous probability distributions are used to model random variables that can take on any real value within a specified range. These variables do not take on isolated or countable values but rather exist on a continuum. For example, the height of an individual can be measured with increasing precision—such as 163.5 or 165.25 centimeters—demonstrating that height is a continuous random variable.The behavior of such variables is described using a probability density function (PDF), which...