In mathematics and statistics, a quantitative variable may be continuous or discrete if they are typically obtained by measuring or counting, respectively. If it can take on two particular real values such that it can also take on all real values between them (even values that are arbitrarily close together), the variable is continuous in that interval. If it can take on a value such that there is a non-infinitesimal gap on each side of it containing no values that the variable can take on, then it is discrete around that value. In some contexts a variable can be discrete in some ranges of the number line and continuous in others. (Wikipedia).
Introduction to Discrete and Continuous Variables
This video defines and provides examples of discrete and continuous variables.
From playlist Introduction to Functions: Function Basics
Random Variable Examples with Discrete and Continuous
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From playlist Statistics
Discrete or Continuous Variable
In this video I explain the difference between discrete and continuous variables.
From playlist Maths B / Methods Course, Grade 11/12, High School, Queensland, Australia.
Discrete versus Continuous Random Variables
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From playlist Statistics
What are Continuous Random Variables? (2 of 3: Why we need different tools)
More resources available at www.misterwootube.com
From playlist Random Variables
Introduction to Discrete and Continuous Functions
This video defines and provides examples of discrete and continuous functions.
From playlist Introduction to Functions: Function Basics
Discrete Data and Continuous Data
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From playlist Statistics
Statistics: Ch 5 Discrete Random Variable (2 of 27) What is a Discrete Random Variable?
Visit http://ilectureonline.com for more math and science lectures! To donate: http://www.ilectureonline.com/donate https://www.patreon.com/user?u=3236071 We will learn a discrete random variable can be a count of something, an integer, as how many times a coin comes up “heads” or “tails
From playlist STATISTICS CH 5 DISCRETE RANDOM VARIABLE
Notation and Basic Signal Properties
http://AllSignalProcessing.com for free e-book on frequency relationships and more great signal processing content, including concept/screenshot files, quizzes, MATLAB and data files. Signals as functions, discrete- and continuous-time signals, sampling, images, periodic signals, displayi
From playlist Introduction and Background
Lecture 19 | The Fourier Transforms and its Applications
Lecture by Professor Brad Osgood for the Electrical Engineering course, The Fourier Transforms and its Applications (EE 261). Professor Osgood demonstrates aliasing by showing the class what happens when you under sample music. The Fourier transform is a tool for solving physical probl
From playlist Lecture Collection | The Fourier Transforms and Its Applications
FRM: Terms about distributions: PDF, PMF and CDF
Distributions characterize random variables. Random variables are either discrete (PMF) or continuous (PDF). About these distributions, we can ask either an "equal to" (PDF/PMF) question or a "less than" question (CDF). But all distributions have the same job: characterize the random varia
From playlist Statistics: Distributions
(PP 3.2) Types of Random Variables
(0:00) Discrete random variables. (1:08) Random variables with densities. (3:35) Decomposition into discrete, absolutely continuous, and singular continuous parts. (7:12) Relationship with discrete & density-type random variables. A playlist of the Probability Primer series is avai
From playlist Probability Theory
Discrete and continuous random variables | Probability and Statistics | Khan Academy
Courses on Khan Academy are always 100% free. Start practicing—and saving your progress—now: https://www.khanacademy.org/math/statistics-probability/random-variables-stats-library/random-variables-discrete/v/discrete-and-continuous-random-variables Defining discrete and continuous random
From playlist Random variables and probability distributions | Probability and Statistics | Khan Academy
8. Continuous Random Variables
MIT 6.041 Probabilistic Systems Analysis and Applied Probability, Fall 2010 View the complete course: http://ocw.mit.edu/6-041F10 Instructor: John Tsitsiklis License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 6.041SC Probabilistic Systems Analysis and Applied Probability, Fall 2013
Discrete & Continuous random variables
Let's talk about discrete and continuous random variables. For more information, check out the blog post on probability fundamentals in Machine Learning: https://towardsdatascience.com/probability-for-machine-learning-b4150953df09 BLOG: https://medium.com/@dataemporium Maximum Likeliho
From playlist The Math You Should Know
MIT RES.6-012 Introduction to Probability, Spring 2018 View the complete course: https://ocw.mit.edu/RES-6-012S18 Instructor: John Tsitsiklis License: Creative Commons BY-NC-SA More information at https://ocw.mit.edu/terms More courses at https://ocw.mit.edu
From playlist MIT RES.6-012 Introduction to Probability, Spring 2018
DISCRETE Random Variables: Finite and Infinite Distributions (9-2)
A Discrete Random Variable is any outcome of a statistical experiment that takes on discrete (i.e., separate and distinct) numerical values. Discrete outcomes: all potential outcomes numerical values are integers (i.e., whole numbers). They cannot be negative. Using an example of tests in
From playlist Discrete Probability Distributions in Statistics (WK 9 - QBA 237)
Prob & Stats - Random Variable & Prob Distribution (4 of 53) Types of Random Variable
Visit http://ilectureonline.com for more math and science lectures! In this video I will define 2 types of random variables (discrete and continuous variables). Next video in series: http://youtu.be/mtt3h54aSkk
From playlist iLecturesOnline: Probability & Stats 2: Random Variable & Probability Distribution