Respuesta :
Answer:
1) [tex] P_o = \frac{125}{e^{2*0.5148097086}}= 44.643 \approx 45[/tex]
2) [tex] P(t) = 44.643 e^{0.5148097086 t}[/tex]
3) [tex] P(t=8) = 44.643 e^{0.5148097086*8}=2744.009 \approx 2744[/tex]
4) [tex] ln(559.998) =0.5148097086 t[/tex]
[tex] t = \frac{ln(559.998)}{0.5148097086}=12.291 hours[/tex]
Step-by-step explanation:
The exponential model on this case is given by the following formula:
[tex] P(t) = P_o e^{kt}[/tex]
Where P represent the population, k the growth/decay constant and t the time in hours for this case.
[tex] P_o[/tex] represent the initial population
We have some initial conditions given:
[tex] P(2) = 125, P(4) = 350[/tex]
Part 1
From the initial conditions we have the following equations:
[tex] 125 = P_o e^{2k}[/tex] (1)
[tex] 350 = P_o e^{4k}[/tex] (2)
We can solve for [tex] P_o [/tex] from equation (1) like this:
[tex] P_o = \frac{125}{e^{2k}}[/tex]
And we can replace this into equation (2) and we got:
[tex] 350 =\frac{125}{e^{2k}} e^{4k} = 125 e^{2k}[/tex]
And we can divide both sides by 125:
[tex] \frac{14}{5} = e^{2k}[/tex]
Now we can apply natural log on both sides and we got:
[tex] ln (\frac{14}{5}) = 2k[/tex]
[tex] k = \frac{ln(14/5)}{2}=0.5148097086[/tex]
And now since we have the value of k we can solve for [tex] P_o[/tex] like this:
[tex] P_o = \frac{125}{e^{2*0.5148097086}}= 44.643 \approx 45[/tex]
Part 2
For this case the exponential model is given by:
[tex] P(t) = 44.643 e^{0.5148097086 t}[/tex]
Part 3
For this case we just need to replace t=8 and see what we got:
[tex] P(t=8) = 44.643 e^{0.5148097086*8}=2744.009 \approx 2744[/tex]
Part 4
For this case we want to solve this:
[tex] 25000 = 44.643 e^{0.5148097086 t}[/tex]
We can divide both sides by 44.643 and we got:
[tex]559.998 = e^{0.5148097086 t}[/tex]
Now we can apply natural logs on both sides:
[tex] ln(559.998) =0.5148097086 t[/tex]
[tex] t = \frac{ln(559.998)}{0.5148097086}=12.291 hours[/tex]