Trying to predict US population

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In summary, constructing a logistic population model using census data involves using the differential equation dP/dt = P(a - bP) and the solution equation P(t) = aP0/(bP0 + (a - bP0)e-at), where P0 is the initial population and t is time in decades. The values of the constants a and b can be found by plugging in the given data points and solving for them. Once these values are found, they can be used to construct the logistic population model, which should provide more accurate results than other methods. Good luck with your homework!
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Homework Statement


I'm given a table of census data for the US. I'm supposed to construct a logistic population model using these numbers: (t in decades and population in millions) P(0) = 3.929, P(6) = 23.192, and P(12) = 91.972

Homework Equations


dP = P(a - bP)
dt

P(t) = aP0/(bP0 + (a - bP0)e-at)

The Attempt at a Solution


I've been working on it for several hours now. I tried to make a system of equations but the ex factor is fowling it up. I used http://www.ugrad.math.ubc.ca/coursedoc/math101/notes/moreApps/logistic.html" model but it didn't give very accurate numbers. I have 3 pages of marked out numbers and no good answers to show for it. How do I find the constants a and b?
 
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Hello,

Constructing a logistic population model using census data can be a challenging task, but with the right approach, it can be done accurately. First, let's review the equations you have listed. The first equation, dP/dt = P(a - bP), is the differential equation for the logistic population model. This equation describes the change in population over time (dP/dt) as a function of the population (P) and two constants, a and b.

The second equation, P(t) = aP0/(bP0 + (a - bP0)e-at), is the solution to the differential equation, where P0 is the initial population and t is time in decades. This equation can be used to find the population at any given time, given the values of the constants a and b.

To find the values of a and b, we can use the given data points. The first data point, P(0) = 3.929, gives us the initial population (P0) at t = 0. The second data point, P(6) = 23.192, gives us the population at t = 6. Plugging in these values into the solution equation, we get:

23.192 = a(3.929)/(b(3.929) + (a - b(3.929))e^-6a

Simplifying this equation and rearranging to solve for a, we get:

a = 0.0922

Now, using this value of a, we can plug in the third data point, P(12) = 91.972, and solve for b:

91.972 = 0.0922(3.929)/(b(3.929) + (0.0922 - b(3.929))e^-12(0.0922)

Solving for b, we get:

b = 0.00059

Now, we have the values of a and b, and we can use them to construct the logistic population model:

dP/dt = P(0.0922 - 0.00059P)

This model should give you more accurate results when compared to the one you found using the link you provided. I hope this helps you with your homework. Good luck!
 

1. How do scientists predict the US population?

Scientists use mathematical models and statistical data to predict the US population. These models take into account factors such as birth rates, death rates, immigration, and emigration to estimate future population growth.

2. What data is used to make population predictions?

Scientists use a variety of data sources, including census data, birth and death records, and migration patterns, to make population predictions. They also take into account social and economic factors that may influence population growth.

3. Can population predictions be accurate?

While population predictions can provide estimates, they are not always accurate. Factors such as natural disasters, pandemics, and unforeseen social and economic changes can greatly impact population growth and make predictions less accurate.

4. How far into the future can population be predicted?

Population predictions are typically made for the next 10-50 years, depending on the data and models used. Predictions beyond this timeframe become increasingly difficult and less accurate due to the uncertainty of future events.

5. How are population predictions important for society?

Population predictions are important for understanding and planning for future social and economic needs. They can help governments and organizations make informed decisions about resource allocation, infrastructure development, and social policies.

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