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shutvik [7]
3 years ago
14

In an isolated environment, a disease spreads at a rate proportional to the product of the infected and non-infected populations

. Let I(t) denote the number of infected individuals. Suppose that the total population is 2000, the proportionality constant is 0.0002, and that 1% of the population is infected at time t=0. Write down the intial value problem and the solution I(t).
Mathematics
1 answer:
eimsori [14]3 years ago
8 0

Answer:

Expression: N = C·L·l(t)· T + 20

The initial value problem and solution are expressed as a first order differential equation.

Step-by-step explanation:

First, gather the information:

total population, N = 2 000

Proportionality constant, C = 0.0002

l(t) number of infected individuals = l(t)

healthy individuals = L

The equation is given as follows:

N = C·L·l(t)

However, there is a change with time, so the expression will be:

\frac{dN}{dt} = C·L·l(t)

multiplying both sides  by dt gives:

dN  =   C·L·l(t)

Integrating both sides gives:

\int\limits^a_b {dN} \, dt = \int\limits^a_b {CLl(t)} \, dt

N = C·L·l(t)· T + K

initial conditions:

T= 0, N₀ = (0.01 ₓ 2 000)  = 20

to find K, plug in the values:

N₀ = K

20 = K

At any time T, the expression will be:

<u>N = C·L·l(t)· T + 20</u> Ans

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Answer:

The probability that the sample mean would be at least $39000 is of 0.8665 = 86.65%.

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal Probability Distribution:

Problems of normal distributions can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the z-score of a measure X is given by:

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The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.

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Mean $39725 and standard deviation $7320.

This means that \mu = 39725, \sigma = 7320

Sample of 125

This means that n = 125, s = \frac{7320}{\sqrt{125}}

The probability that the sample mean would be at least $39000 is about?

This is 1 subtracted by the pvalue of Z when X = 39000. So

Z = \frac{X - \mu}{\sigma}

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{39000 - 39725}{\frac{7320}{\sqrt{125}}}

Z = -1.11

Z = -1.11 has a pvalue of 0.1335

1 - 0.1335 = 0.8665

The probability that the sample mean would be at least $39000 is of 0.8665 = 86.65%.

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