Consider the outcomes of a coin tossed as a random event. The probability of getting tail is 1 2 or 50%, and the probability of getting head is 1 2 or 50% also, but it is hard to predict the outcome that will occur. In this lesson, you will learn how to determine the likeliness of the happening of an event. What’s New Mean of a Discrete Random Variable The Mean µ of a discrete random variable is the central value or average of its corresponding probability mass function. It is also called as the Expected Value. It is computed using the formula : µ = ∑ ??(?) Where x is the outcome and p(x) is the probability of the outcome .
Consider the outcomes of a coin tossed as a random event. The probability of getting tail is 1 2 or 50%, and the probability of getting head is 1 2 or 50% also, but it is hard to predict the outcome that will occur. In this lesson, you will learn how to determine the likeliness of the happening of an event. What’s New Mean of a Discrete Random Variable The Mean µ of a discrete random variable is the central value or average of its corresponding probability mass function. It is also called as the Expected Value. It is computed using the formula : µ = ∑ ??(?) Where x is the outcome and p(x) is the probability of the outcome .
A First Course in Probability (10th Edition)
10th Edition
ISBN:9780134753119
Author:Sheldon Ross
Publisher:Sheldon Ross
Chapter1: Combinatorial Analysis
Section: Chapter Questions
Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...
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Question
Consider the outcomes of a coin tossed as a random event . The probability of
getting tail is
1
2
or 50%, and the probability of getting head is
1
2
or 50% also, but
it is hard to predict the outcome that will occur. In this lesson, you will learn how
to determine the likeliness of the happening of an event.
What’s New
Mean of a Discrete Random Variable
The Mean µ of a discrete random variable is the central value or
average of its corresponding probability mass function . It is also called
as the Expected Value . It is computed using the formula
:
µ = ∑ ??(?)
Where x is the outcome and p(x) is the probability of the outcome
.
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