If the distribution function of X is given byfor x <2for 2sx<336for 3sx<436for 4 sx<53610for 5sx<63615for 6sx <7F(x)21for 7sx<83626for 8 sx <930for 9sx <10for 10=x<113635for 11sx <12for x 2 1236find the probability distribution of this random variable.

A discrete random variable has only discrete values which can be counted. For example a random…

Answered: If the distribution function of X is…

If the distribution function of X is given by for x <2 for 2sx<3 36 for 3sx<4 for 4sx <5 36 for 5 sx <6 36 15 36 for 6sx<7 F(x) = 21 for 7

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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Concept explainers

Continuous Probability Distributions

Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.

Normal Distribution

Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!

Question

100%

If the distribution function of X is given by
for x <2
for 2sx<3
36
for 3sx<4
36
for 4 sx<5
36
10
for 5sx<6
36
15
for 6sx <7
F(x)
21
for 7sx<8
36
26
for 8 sx <9
30
for 9sx <10
for 10=x<11
36
35
for 11sx <12
for x 2 12
36
find the probability distribution of this random variable.

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