Discrete Random Variables Assignment Help

A random variable is one that contains the results of a random experiment. Assume an experiment in which the arrivals of automobiles at a turnpike tollbooth are measured over a 30-second period. The following outcomes are possible: 0 cars, 1 cars, 2 cars,…, n cars. These are the values of a random variable (0, 1, 2,…, n). Assume another experiment is to time the completion of two tasks on a production line. The values will range between 0 and n seconds. The values of another random variable are represented by these time measurements.

KEY FEATURE

Discrete random variables have a limited number of values. The result of rolling a die, for example, is a discrete random variable because it can only land on one of six possible numbers.

A discrete random variable is one that can only have a finite number of distinct values, such as 0, 1, 2, 3, 4, etc. Discrete random variables are typically (but not always) counts.

A random variable must be discrete if it can only take a finite number of distinct values. The number of children in a family, the number of Friday night moviegoers are examples of It.

A discrete random variable’s probability distribution is a list of probabilities associated with each of its possible values. It is also known as the probability function or probability mass function.

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Key Topics

    The two types of random variables are as follows:

    1- Variables with discrete randomness
    2- Variables with continuous randomness
    A discrete random variable has at most a finite or countably infinite number of possible values in its set of all possible values.
    Continuous random variables are assigned values at each point along a given interval.
    Random variable outcomes and associated probabilities can be organised into distributions. There are two types of distributions: discrete distributions, which are made up of discrete random variables, and continuous distributions, which are made up of continuous random variables.
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    A discrete random variable is one that can only take the values that are countable in nature. If the total sum of the probabilities equals one, the variable is considered random. As a result, a discrete variable is one whose value can be determined by counting. Examples include the total number of students in the class, the number of black marbles in the box, and so on.
    This concept is broad and includes a variety of activities such as studying the meaning, analysing various associated theories, understanding probability, graphs, numerical questions and equations, and many others
    When dealing with discrete random variables, their probability distribution can be represented using tables, formulas, and graphical techniques. It will aid in providing all possible values as well as the probability associated with each value.
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