Calculating Logistic Growth Rate

In summary, the logistic growth problem is finding the growth rate for an exponentially growing X, given the year Y.
  • #1
andre6051
1
0
I have a logistic growth problem. I know this because there is an upper limit of approximately 21,000 people. I need to calculate growth rate. Would it be something as simple as taking two populations and dividing them to get the rate (X2-X1/X1) to obtain it or is there an equation I am missing? I feel like the growth rate is harder to find than that. Plus, for some reason, the number shot up in 2015 and I don't know what to do. The only info I have is below. Thanks!

Example

X Y
44 2010
61 2011
79 2012
208 2013
326 2014
6663 2015
 
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  • #2
andre6051 said:
I have a logistic growth problem. I know this because there is an upper limit of approximately 21,000 people. I need to calculate growth rate. Would it be something as simple as taking two populations and dividing them to get the rate (X2-X1/X1) to obtain it or is there an equation I am missing? I feel like the growth rate is harder to find than that. Plus, for some reason, the number shot up in 2015 and I don't know what to do. The only info I have is below. Thanks!

Example

X Y
44 2010
61 2011
79 2012
208 2013
326 2014
6663 2015

Hi andre6051! Welcome to MHB! (Smile)

It looks like Y is a year and X increases exponentially.
So the relevant equation would be $X=AB^Y$ so that $\frac {X_2}{X_1} = \frac{AB^{Y_2}}{AB^{Y_1}} = B^{Y_2 - Y_1}$.
For successive years that means $B = \frac {X_2}{X_1}$.

It also means that $\log X = \log A + Y \log B$.
Typically we would find a linear regression between $\log X$ and $Y$ to figure out the relation.

Then again, as you already noticed, in 2015 the number shot up, causing an outlier.
We should get more information why that is, since it may mean we can't treat it as a logistic growth problem.
Can it be that the last X should really be, say, 663? Maybe there is a typo...
 

FAQ: Calculating Logistic Growth Rate

What is logistic growth rate?

Logistic growth rate is a mathematical model that describes how a population grows over time, taking into account limiting factors such as available resources and carrying capacity. It is used to predict population growth in natural sciences and to analyze data in social sciences.

How is logistic growth rate calculated?

Logistic growth rate is calculated using the logistic growth equation, which takes into account the initial population size, the intrinsic growth rate, and the carrying capacity of the environment. The equation is: dN/dt = rN(1 - N/K), where dN/dt is the change in population over time, r is the intrinsic growth rate, N is the current population size, and K is the carrying capacity.

What is the difference between logistic growth rate and exponential growth rate?

The main difference between logistic growth rate and exponential growth rate is that logistic growth takes into account limiting factors, while exponential growth assumes unlimited resources. In logistic growth, the population growth rate slows down as it approaches the carrying capacity, while in exponential growth, the population continues to grow at a constant rate.

What are some real-world examples of logistic growth?

Logistic growth can be observed in many natural populations, such as animal populations in an ecosystem. For example, the growth of a deer population in a forest will eventually reach a point where the available resources, such as food and space, become limited and the population growth slows down. Logistic growth can also be seen in human populations, with birth rates and death rates being influenced by factors such as access to healthcare and education.

What are the limitations of using logistic growth rate?

One limitation of using logistic growth rate is that it assumes a constant carrying capacity, which may not always be the case in real-world situations. Environmental changes or human interventions can affect the carrying capacity, leading to inaccurate predictions. Additionally, the logistic growth model does not take into account short-term fluctuations and assumes a smooth growth pattern, which may not always be the case in nature.

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