Let X be a random variable such that X Tr(-1,1,0). ~ a. Find the pdf of X, fx(x). b. Find the cdf of X, Fx(x) c. Find P(-/ < X <-). d. Find E[X] e. Find Var[X]

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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Please do all parts and show your work MODE means the value of x where pdf is maximized
Here is a picture of the pdf of a triangular distribution
Tr(a, b, c) whose support is (a,b) and whose mode is c.
2
b-a
a
C
b
Transcribed Image Text:Here is a picture of the pdf of a triangular distribution Tr(a, b, c) whose support is (a,b) and whose mode is c. 2 b-a a C b
Let X be a random variable such that X~ Tr(-1,1,0).
a. Find the pdf of X, fx(x).
b. Find the cdf of X, Fx(x)
c. Find P(-/ < X < =).
d. Find E[X]
e. Find Var[X]
Transcribed Image Text:Let X be a random variable such that X~ Tr(-1,1,0). a. Find the pdf of X, fx(x). b. Find the cdf of X, Fx(x) c. Find P(-/ < X < =). d. Find E[X] e. Find Var[X]
Expert Solution
Step 1: Basic concept needed to solve this problem

The problem we're dealing with involves a continuous random variable X that follows a triangular distribution with specific parameters: a lower bound (a), an upper bound (b), and a mode (c). Here are some basic concepts and steps to understand and solve this problem:

  1. Triangular Distribution: The triangular distribution is characterized by three parameters - a, b, and c, which represent the lower bound, upper bound, and mode (peak), respectively. It's called "triangular" because its probability density function (pdf) has a triangular shape.

  2. Probability Density Function (pdf): The pdf describes the probability of X taking on a particular value. For the triangular distribution, the pdf has different expressions in different regions of the variable's range.

  3. Cumulative Distribution Function (cdf): The cdf represents the probability that X is less than or equal to a specific value. It is calculated by integrating the pdf.

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