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Sladkaya [172]
3 years ago
5

Consider a population of bacteria that grows according to the initial value problem dP/dt=P/10, P(0)=300. Find the population si

ze after 40 hours
Mathematics
1 answer:
kozerog [31]3 years ago
6 0

 dP / dt = P / 10
 We apply separable variables:
 dP / P = dt / 10
 We integrate both sides:
 Ln (P) = t / 10 + C
 We rewrite the equation:
 Exp (Ln (P)) = Exp (t / 10 + C)
 P = Exp (C) * Exp (t / 10)
 P = C * Exp (t / 10)
 We look for the constant using:
 P (0) = 300
 300 = C * Exp (0/10)
 300 = C * 1
 C = 300
 We rewrite the equation:
 P = 300 * Exp (t / 10)
 After 40 hours we have:
 P = 300 * Exp (40/10)
 P = 16379.44501
 Answer:
 the population size after 40 hours is: 
 P = 16379
You might be interested in
Suppose the number of children in a household has a binomial distribution with parameters n=12n=12 and p=50p=50%. Find the proba
nadya68 [22]

Answer:

a) 20.95% probability of a household having 2 or 5 children.

b) 7.29% probability of a household having 3 or fewer children.

c) 19.37% probability of a household having 8 or more children.

d) 19.37% probability of a household having fewer than 5 children.

e) 92.71% probability of a household having more than 3 children.

Step-by-step explanation:

Binomial probability distribution

The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

In which C_{n,x} is the number of different combinations of x objects from a set of n elements, given by the following formula.

C_{n,x} = \frac{n!}{x!(n-x)!}

And p is the probability of X happening.

In this problem, we have that:

n = 12, p = 0.5

(a) 2 or 5 children

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

P(X = 2) = C_{12,2}.(0.5)^{2}.(0.5)^{10} = 0.0161

P(X = 5) = C_{12,5}.(0.5)^{5}.(0.5)^{7} = 0.1934

p = P(X = 2) + P(X = 5) = 0.0161 + 0.1934 = 0.2095

20.95% probability of a household having 2 or 5 children.

(b) 3 or fewer children

P(X \leq 3) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3)

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

P(X = 0) = C_{12,0}.(0.5)^{0}.(0.5)^{12} = 0.0002

P(X = 1) = C_{12,1}.(0.5)^{1}.(0.5)^{11} = 0.0029

P(X = 2) = C_{12,2}.(0.5)^{2}.(0.5)^{10} = 0.0161

P(X = 3) = C_{12,3}.(0.5)^{3}.(0.5)^{9} = 0.0537

P(X \leq 3) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3) = 0.0002 + 0.0029 + 0.0161 + 0.0537 = 0.0729

7.29% probability of a household having 3 or fewer children.

(c) 8 or more children

P(X \geq 8) = P(X = 8) + P(X = 9) + P(X = 10) + P(X = 11) + P(X = 12)

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

P(X = 8) = C_{12,8}.(0.5)^{8}.(0.5)^{4} = 0.1208

P(X = 9) = C_{12,9}.(0.5)^{9}.(0.5)^{3} = 0.0537

P(X = 10) = C_{12,10}.(0.5)^{10}.(0.5)^{2} = 0.0161

P(X = 11) = C_{12,11}.(0.5)^{11}.(0.5)^{1} = 0.0029

P(X = 12) = C_{12,12}.(0.5)^{12}.(0.5)^{0} = 0.0002

P(X \geq 8) = P(X = 8) + P(X = 9) + P(X = 10) + P(X = 11) + P(X = 12) = 0.1208 + 0.0537 + 0.0161 + 0.0029 + 0.0002 = 0.1937

19.37% probability of a household having 8 or more children.

(d) fewer than 5 children

P(X < 5) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3) + P(X = 4)

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

P(X = 0) = C_{12,0}.(0.5)^{0}.(0.5)^{12} = 0.0002

P(X = 1) = C_{12,1}.(0.5)^{1}.(0.5)^{11} = 0.0029

P(X = 2) = C_{12,2}.(0.5)^{2}.(0.5)^{10} = 0.0161

P(X = 3) = C_{12,3}.(0.5)^{3}.(0.5)^{9} = 0.0537

P(X = 4) = C_{12,4}.(0.5)^{4}.(0.5)^{8} = 0.1208

P(X < 5) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3) + P(X = 4) = 0.0002 + 0.0029 + 0.0161 + 0.0537 + 0.1208 = 0.1937

19.37% probability of a household having fewer than 5 children.

(e) more than 3 children

Either a household has 3 or fewer children, or it has more than 3. The sum of these probabilities is 100%.

From b)

7.29% probability of a household having 3 or fewer children.

p + 7.29 = 100

p = 92.71

92.71% probability of a household having more than 3 children.

5 0
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Fourteen thousand seven hundred ninety three in standard form
NeTakaya

Answer:

14,793

Step-by-step explanation:

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