Q4 In this question, the real numbers in your answers should be given with three significant digits of accuracy after the decimal point. The public health authorities of a small town have divided the population into three categories: covid-negative, covid-positive, and hospitalised. After performing regular, extensive tests, they have observed that in each successive week: Among those who are negative, 95% remain so, 4% become positive, and 1% need to be hospitalised. Among those who are positive, 75% recover and become negative, 20% stay positive, and 5% need to be hospitalised. Among those who are hospitalised, 60% recover and become negative, 30% are released from hospital but remain positive, and 10% remain hospitalised.
Q4 In this question, the real numbers in your answers should be given with three significant digits of accuracy after the decimal point. The public health authorities of a small town have divided the population into three categories: covid-negative, covid-positive, and hospitalised. After performing regular, extensive tests, they have observed that in each successive week: Among those who are negative, 95% remain so, 4% become positive, and 1% need to be hospitalised. Among those who are positive, 75% recover and become negative, 20% stay positive, and 5% need to be hospitalised. Among those who are hospitalised, 60% recover and become negative, 30% are released from hospital but remain positive, and 10% remain hospitalised.
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
![(a) After representing the population in a given week as a column
vector v =
[n; p; h], where n, p, and h represent the number of
people in the population who are negative, positive, and
hospitalised respectively, write down a matrix M for which
[n', p', h'] = M[n; p; h], where [n', p' , h'] represents the
column vector of negative, positive, and hospitalised members of
the population in the following week.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fb90e355c-abe9-45d7-b8d1-631ace6b1e69%2F3947e156-0e48-4e4c-bbde-4295eb150a59%2F3eiby2n_processed.png&w=3840&q=75)
Transcribed Image Text:(a) After representing the population in a given week as a column
vector v =
[n; p; h], where n, p, and h represent the number of
people in the population who are negative, positive, and
hospitalised respectively, write down a matrix M for which
[n', p', h'] = M[n; p; h], where [n', p' , h'] represents the
column vector of negative, positive, and hospitalised members of
the population in the following week.
![Q4
In this question, the real numbers in your answers should be given
with three significant digits of accuracy after the decimal point.
The public health authorities of a small town have divided the
population into three categories: covid-negative, covid-positive,
and hospitalised. After performing regular, extensive tests, they
have observed that in each successive week:
Among those who are negative, 95% remain so, 4% become
positive, and 1% need to be hospitalised.
Among those who are positive, 75% recover and become
negative, 20% stay positive, and 5% need to be hospitalised.
Among those who are hospitalised, 60% recover and become
negative, 30% are released from hospital but remain positive,
and 10% remain hospitalised.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fb90e355c-abe9-45d7-b8d1-631ace6b1e69%2F3947e156-0e48-4e4c-bbde-4295eb150a59%2Fbdk3q7x_processed.png&w=3840&q=75)
Transcribed Image Text:Q4
In this question, the real numbers in your answers should be given
with three significant digits of accuracy after the decimal point.
The public health authorities of a small town have divided the
population into three categories: covid-negative, covid-positive,
and hospitalised. After performing regular, extensive tests, they
have observed that in each successive week:
Among those who are negative, 95% remain so, 4% become
positive, and 1% need to be hospitalised.
Among those who are positive, 75% recover and become
negative, 20% stay positive, and 5% need to be hospitalised.
Among those who are hospitalised, 60% recover and become
negative, 30% are released from hospital but remain positive,
and 10% remain hospitalised.
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