Consider a continuous random variable X with the following PDF: {: -1 ≤ x ≤0 or 1≤ x ≤ 3 otherwise (a) Sketch the PDF of X. Be sure to label your axes. (b) Determine the value of c that satisfies the normalization property. Set c to this value for the remainder of the problem. This can be done without integration, so your answer should be a number. fx(x) (c) What is the expected value of X? (d) What is the variance of X? (e) What is E[2X² - 3X + 1]? (f) Calculate the probability that X| is less than 2. (Your answer can be an integral, but you can also take advantage of the simple structure of the PDF.) (g) Let B = (−2,2). Determine the conditional PDF fx|Â(x) of X given the event {X € B}. (h) Calculate the probability that X < 0 given that X is less than 2. (i) Calculate the conditional expectation E[X|B] of X given that X is less than 2.
Consider a continuous random variable X with the following PDF: {: -1 ≤ x ≤0 or 1≤ x ≤ 3 otherwise (a) Sketch the PDF of X. Be sure to label your axes. (b) Determine the value of c that satisfies the normalization property. Set c to this value for the remainder of the problem. This can be done without integration, so your answer should be a number. fx(x) (c) What is the expected value of X? (d) What is the variance of X? (e) What is E[2X² - 3X + 1]? (f) Calculate the probability that X| is less than 2. (Your answer can be an integral, but you can also take advantage of the simple structure of the PDF.) (g) Let B = (−2,2). Determine the conditional PDF fx|Â(x) of X given the event {X € B}. (h) Calculate the probability that X < 0 given that X is less than 2. (i) Calculate the conditional expectation E[X|B] of X given that X is less than 2.
A First Course in Probability (10th Edition)
10th Edition
ISBN:9780134753119
Author:Sheldon Ross
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Chapter1: Combinatorial Analysis
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![Consider a continuous random variable X with the following PDF:
ſc −1≤x≤ 0 or 1 ≤ x ≤ 3
- {%
otherwise
(a) Sketch the PDF of X. Be sure to label your axes.
(b) Determine the value of c that satisfies the normalization property. Set c to this value for
the remainder of the problem. This can be done without integration, so your answer should
be a number.
fx(x)=
(c) What is the expected value of X?
(d) What is the variance of X?
(e) What is E[2X² - 3X + 1]?
(f) Calculate the probability that |X| is less than 2. (Your answer can be an integral, but you
can also take advantage of the simple structure of the PDF.)
(g) Let B
=
(-2,2). Determine the conditional PDF fx|B(x) of X given the event {X € B}.
(h) Calculate the probability that X < 0 given that X is less than 2.
(i) Calculate the conditional expectation E[X|B] of X given that |X| is less than 2.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F02681530-b6ca-4d72-bfd1-7260256101ab%2Fffef05df-c6ca-475b-8740-aa508ff5ad99%2F0t0dihs_processed.png&w=3840&q=75)
Transcribed Image Text:Consider a continuous random variable X with the following PDF:
ſc −1≤x≤ 0 or 1 ≤ x ≤ 3
- {%
otherwise
(a) Sketch the PDF of X. Be sure to label your axes.
(b) Determine the value of c that satisfies the normalization property. Set c to this value for
the remainder of the problem. This can be done without integration, so your answer should
be a number.
fx(x)=
(c) What is the expected value of X?
(d) What is the variance of X?
(e) What is E[2X² - 3X + 1]?
(f) Calculate the probability that |X| is less than 2. (Your answer can be an integral, but you
can also take advantage of the simple structure of the PDF.)
(g) Let B
=
(-2,2). Determine the conditional PDF fx|B(x) of X given the event {X € B}.
(h) Calculate the probability that X < 0 given that X is less than 2.
(i) Calculate the conditional expectation E[X|B] of X given that |X| is less than 2.
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