What Is The Difference Btween A Discrenet And Continuos Pdf

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Discrete vs continuous data

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Mathematics Stack Exchange is a question and answer site for people studying math at any level and professionals in related fields. It only takes a minute to sign up. Can someone provide me a clear explanation Perhaps with examples about the difference between the following mathematical three concepts in probability :. A discrete random variable is a random variable which takes on at most countably many values. In particular, any random variable that takes on finitely many values is discrete. An example is the sum of two die rolls.

A continuous distribution describes the probabilities of the possible values of a continuous random variable. A continuous random variable is a random variable with a set of possible values known as the range that is infinite and uncountable. Probabilities of continuous random variables X are defined as the area under the curve of its PDF. Thus, only ranges of values can have a nonzero probability. The probability that a continuous random variable equals some value is always zero.

Difference Between Discrete and Continuous Variable

Variable refers to the quantity that changes its value, which can be measured. It is of two types, i. The former refers to the one that has a certain number of values, while the latter implies the one that can take any value between a given range. Data can be understood as the quantitative information about a specific characteristic. The characteristic can be qualitative or quantitative, but for the purpose of statistical analysis, the qualitative characteristic is transformed into quantitative one, by providing numerical data of that characteristic.

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A continuous r.v. can take any value in some A probability distribution for a discrete r.v. X How do we describe and compare X and Y? function (PDF).


What is the difference between a discrete random variable and a continuous random variable?

In probability and statistics, a randomvariable is a variable whose value is subject to variations due to chance i. As opposed to other mathematical variables, a random variable conceptually does not have a single, fixed value even if unknown ; rather, it can take on a set of possible different values, each with an associated probability. Random variables can be classified as either discrete that is, taking any of a specified list of exact values or as continuous taking any numerical value in an interval or collection of intervals. The mathematical function describing the possible values of a random variable and their associated probabilities is known as a probability distribution. Discrete random variables can take on either a finite or at most a countably infinite set of discrete values for example, the integers.

A discrete random variable has a finite number of possible values. A continuous random variable could have any value usually within a certain range. A discrete random variable is typically an integer although it may be a rational fraction. As an example of a discrete random variable: the value obtained by rolling a standard 6-sided die is a discrete random variable having only the possible values: 1, 2, 3, 4, 5, and 6.

Sign in. Random Variables play a vital role in probability distributions and also serve as the base for Probability distributions. Before we start I would highly recommend you to go through the blog — understanding of random variables for understanding the basics.

Difference Between Discrete and Continuous Variable

What is discrete data?

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Probability Distributions: Discrete and Continuous

 Потрясающе, - страдальчески сказал директор.  - У вас, часом, нет такой же под рукой. - Не в этом дело! - воскликнула Сьюзан, внезапно оживившись.

1 Response
  1. Judith H.

    All probability distributions can be classified as discrete probability distributions or as continuous probability distributions, depending on whether they define probabilities associated with discrete variables or continuous variables.

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