/*! This file is auto-generated */ .wp-block-button__link{color:#fff;background-color:#32373c;border-radius:9999px;box-shadow:none;text-decoration:none;padding:calc(.667em + 2px) calc(1.333em + 2px);font-size:1.125em}.wp-block-file__button{background:#32373c;color:#fff;text-decoration:none} Q19E Let \({\rm{X}}\) be a continuous... [FREE SOLUTION] | 91影视

91影视

Let \({\rm{X}}\) be a continuous \({\rm{rv}}\) with cdf

\({\rm{F(x) = }}\left\{ {\begin{array}{*{20}{c}}{\rm{0}}&{{\rm{x}} \le {\rm{0}}}\\{\frac{{\rm{x}}}{{\rm{4}}}\left( {{\rm{1 + ln}}\left( {\frac{{\rm{4}}}{{\rm{x}}}} \right)} \right)}&{{\rm{0 < x}} \le {\rm{4}}}\\{\rm{1}}&{{\rm{x > 4}}}\end{array}} \right.\)

(This type of cdf is suggested in the article 鈥淰ariability in Measured Bedload Transport Rates鈥 (Water 91影视 Bull., \({\rm{1985:39 - 48}}\)) as a model for a certain hydrologic variable.) What is a. \({\rm{P(X}} \le {\rm{1)}}\)? b. \({\rm{P(1}} \le {\rm{X}} \le {\rm{3)}}\)? c. The pdf of \({\rm{X}}\)?

Short Answer

Expert verified

(a) The value is \({\rm{0}}{\rm{.5966}}\).

(b) The value is\({\rm{0}}{\rm{.3692}}\).

(c) The function is \({\rm{f(x) = }}\left\{ {\begin{array}{*{20}{l}}{\frac{{\rm{1}}}{{\rm{4}}}\left( {{\rm{ln}}\frac{{\rm{4}}}{{\rm{x}}}} \right)}&{{\rm{0 < x}} \le {\rm{4}}}\\{\rm{0}}&{{\rm{ otherwise }}}\end{array}} \right.\).

Step by step solution

01

Define variable

An unknown number, unknown value, or unknown quantity is represented by a variable, which is an alphabet or word. In the context of algebraic expressions or algebra, the variables are particularly useful.

02

Explanation

(a) The format of cdf is as follows:

\({\rm{F(x) = }}\left\{ {\begin{array}{*{20}{l}}{\rm{0}}&{{\rm{x < 0}}}\\{\frac{{\rm{x}}}{{\rm{4}}}\left( {{\rm{1 + ln}}\frac{{\rm{4}}}{{\rm{x}}}} \right){\rm{0 < x}} \le {\rm{4}}}&{}\\{\rm{1}}&{{\rm{x > 4}}}\end{array}} \right.\)

We can write the following using the proposition and the given cdf:

\(\begin{aligned}{\rm{P(X}} \le 1) &= F(1)\\ &= \frac{{\rm{1}}}{{\rm{4}}}\left( {{\rm{1 + ln}}\frac{{\rm{4}}}{{\rm{1}}}} \right)\\&= \frac{{\rm{1}}}{{\rm{4}}}{\rm{(1 + 1}}{\rm{.3863)}}\\&= \frac{{{\rm{2}}{\rm{.3863}}}}{{\rm{4}}}\\{\rm{P(X}} \le 1) &= 0{\rm{.5966}}\end{aligned}\)

Let X be a continuous\({\rm{rv}}\)with pdf\({\rm{f(x)}}\)and cdf\({\rm{F}}\)as parameters\({\rm{(x)}}\). After that, for any number a,

\({\rm{P(X}} \le {\rm{a) = F(a)}}\)

Therefore, the value is \({\rm{0}}{\rm{.5966}}\).

03

Explanation

(b) Using the following proposition and the provided cdf, we can write:

\(\begin{aligned}{\rm{P(1}} \le {\rm{X}} \le 3) &= F(3) - F(1)\\ & = \frac{{\rm{3}}}{{\rm{4}}}\left( {{\rm{1 + ln}}\frac{{\rm{4}}}{{\rm{3}}}} \right){\rm{ - }}\frac{{\rm{1}}}{{\rm{4}}}\left( {{\rm{1 + ln}}\frac{{\rm{4}}}{{\rm{1}}}} \right)\\& = \frac{{\rm{3}}}{{\rm{4}}}{\rm{(1 + 0}}{\rm{.2877) - }}\frac{{\rm{1}}}{{\rm{4}}}{\rm{(1 + 1}}{\rm{.3863)}}\\ & = \frac{{{\rm{3}}{\rm{.8631}}}}{{\rm{4}}}{\rm{ - }}\frac{{{\rm{2}}{\rm{.3863}}}}{{\rm{4}}}\\ & = 0 {\rm{.9658 - 0}}{\rm{.5966}}\\{\rm{P(1}} \le {\rm{X}} \le 3) &= 0 {\rm{.3692}}\end{aligned}\)

Let X be a continuous\({\rm{rv}}\)with pdf\({\rm{f(x)}}\)and cdf\({\rm{F}}\)as a proposition\({\rm{(x)}}\). Then, using\({\rm{a < b}}\), for any two numbers a and b,

\({\rm{P(a}} \le {\rm{X}} \le {\rm{b) = F(b) - F(a)}}\)

Therefore, the value is \({\rm{0}}{\rm{.3692}}\).

04

Explanation

(c) The proposition presented below is used to determine \({\rm{f(x)}}\):

Proposition: If\({\rm{X}}\)is a continuous\({\rm{rv}}\)with pdf\({\rm{f(x)}}\)and cdf\({\rm{F(x)}}\), the derivative\({{\rm{F}}^{\rm{'}}}{\rm{(x)}}\)exists at every x.

\({\rm{f(x) = F'(x)}}\)

In the intervals\({\rm{x}} \le {\rm{0}}\)and\({\rm{x > 4}}\),\({\rm{F(x)}}\)is constant, hence\({\rm{f(x) = 0}}\)in these intervals.

For any x in the\({\rm{0 < x}} \le {\rm{4}}\)interval:

\(\begin{aligned}f(x) &= {{\rm{F}}^{\rm{'}}}{\rm{(X)}}\\ &= \frac{{\rm{1}}}{{\rm{4}}}\left( {{\rm{1 + ln}}\frac{{\rm{4}}}{{\rm{x}}}} \right){\rm{ + }}\frac{{\rm{x}}}{{\rm{4}}}\left( {\frac{{\rm{x}}}{{\rm{4}}}} \right){\rm{ \times }}\left( {\frac{{{\rm{ - 4}}}}{{{{\rm{x}}^{\rm{2}}}}}} \right)\\ &= \frac{{\rm{1}}}{{\rm{4}}}\left( {{\rm{1 + ln}}\frac{{\rm{4}}}{{\rm{x}}}} \right){\rm{ - }}\frac{{\rm{1}}}{{\rm{4}}}\\f(x) &= \frac{{\rm{1}}}{{\rm{4}}}\left( {{\rm{ln}}\frac{{\rm{4}}}{{\rm{x}}}} \right)\end{aligned}\)

Finally,\({\rm{f(x)}}\)can be written as:

\({\rm{f(x) = }}\left\{ {\begin{array}{*{20}{l}}{\frac{{\rm{1}}}{{\rm{4}}}\left( {{\rm{ln}}\frac{{\rm{4}}}{{\rm{x}}}} \right)}&{{\rm{0 < x}} \le {\rm{4}}}\\{\rm{0}}&{{\rm{ otherwise }}}\end{array}} \right.\)

Unlock Step-by-Step Solutions & Ace Your Exams!

  • Full Textbook Solutions

    Get detailed explanations and key concepts

  • Unlimited Al creation

    Al flashcards, explanations, exams and more...

  • Ads-free access

    To over 500 millions flashcards

  • Money-back guarantee

    We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with 91影视!

One App. One Place for Learning.

All the tools & learning materials you need for study success - in one app.

Get started for free

Most popular questions from this chapter

The article "Microwave Observations of Daily Antarctic Sea-Ice Edge Expansion and Contribution Rates" (IEEE Geosci. and Remote Sensing Letters,\({\rm{2006: 54 - 58}}\)) states that "The distribution of the daily sea-ice advance/retreat from each sensor is similar and is approximately double exponential." The proposed double exponential distribution has density function \({\rm{f(x) = }}{\rm{.5\lambda }}{{\rm{e}}^{{\rm{ - \lambda lel }}}}\)for\( - \yen < x < \yen \). The standard deviation is given as\({\rm{40}}{\rm{.9\;km}}\).

a. What is the value of the parameter\({\rm{\lambda }}\)?

b. What is the probability that the extent of daily sea ice change is within \({\rm{1}}\) standard deviation of the mean value?

Suppose that blood chloride concentration (mmol/L) has a normal distribution with mean\({\rm{104}}\)and standard deviation\({\rm{5}}\)(information in the article "Mathematical Model of Chloride Concentration in Human Blood," \({\rm{J}}\). of Med. Engr. and Tech.,\({\rm{2006: 25 - 30}}\), including a normal probability plot as described in Section\({\rm{4}}{\rm{.6}}\), supports this assumption).

a. What is the probability that chloride concentration equals\({\rm{105}}\)? Is less than\({\rm{105}}\)? Is at most\({\rm{105}}\)?

b. What is the probability that chloride concentration differs from the mean by more than 1 standard deviation? Does this probability depend on the values of\({\rm{\mu }}\)and\({\rm{\sigma }}\)?

c. How would you characterize the most extreme\({\rm{.1\% }}\)of chloride concentration values?

Suppose the reaction temperature \({\rm{X}}\) (in \(^{\rm{o}}{\rm{C}}\)) in a certain chemical process has a uniform distribution with \({\rm{A = - 5}}\) and \({\rm{B = 5}}\).

a. Compute \({\rm{P(X < 0)}}\).

b. Compute \({\rm{P( - 2}}{\rm{.5 < X < 2}}{\rm{.5)}}\).

c. Compute \({\rm{P( - 2}} \le {\rm{X}} \le {\rm{3)}}\).

d. For \({\rm{k}}\) satisfying \({\rm{ - 5 < k < k + 4 < 5}}\), compute \({\rm{P(k < X < k + 4)}}\).

A machine that produces ball bearings has initially been set so that the true average diameter of the bearings it produces is \({\rm{.500}}\)in. A bearing is acceptable if its diameter is within \({\rm{.004}}\)in. of this target value. Suppose, however, that the setting has changed during the course of production, so that the bearings have normally distributed diameters with mean value \({\rm{.499}}\)in. and standard deviation \({\rm{.002}}\)in. What percentage of the bearings produced will not be acceptable?

The current in a certain circuit as measured by an ammeter is a continuous random variable \({\rm{X}}\) with the following density function:

\({\rm{f(x) = \{ }}\begin{array}{*{20}{c}}{{\rm{.075x + }}{\rm{.2}}}&{{\rm{3}} \le {\rm{x}} \le {\rm{5}}}\\{\rm{0}}&{{\rm{otherwise}}}\end{array}\)

a. Graph the pdf and verify that the total area under the density curve is indeed \({\rm{1}}\).

b. Calculate \({\rm{P(X}} \le {\rm{4)}}\). How does this probability compare to \({\rm{P(X < 4)}}\)?

c. Calculate \({\rm{P(3}}{\rm{.5}} \le {\rm{X}} \le {\rm{4}}{\rm{.5)}}\) and also \({\rm{P(4}}{\rm{.5 < X)}}\).

See all solutions

Recommended explanations on Math Textbooks

View all explanations

What do you think about this solution?

We value your feedback to improve our textbook solutions.

Study anywhere. Anytime. Across all devices.