A more refined model of measuring a population of bacteria or cancer cells is the logistic growth model. In this model, dN dt = rN(1 − N/K) , where r and K are constants called the intrinsic growth rate and carrying capacity. The carrying capacity is a measure of limited resources such as food and physical space provided by the environment. This model can also be applied in studying chemical reaction rates and the spread of disease. Any function N(t) = (K)/(1 + (K−N0 )/N0)e-rt , with N0 a nonzero initial population satisfies the logistic model. Verify that N(0) = N0
A more refined model of measuring a population of bacteria or cancer cells is the logistic growth model. In this model, dN dt = rN(1 − N/K) , where r and K are constants called the intrinsic growth rate and carrying capacity. The carrying capacity is a measure of limited resources such as food and physical space provided by the environment. This model can also be applied in studying chemical reaction rates and the spread of disease. Any function N(t) = (K)/(1 + (K−N0 )/N0)e-rt , with N0 a nonzero initial population satisfies the logistic model. Verify that N(0) = N0
Chapter6: Exponential And Logarithmic Functions
Section6.8: Fitting Exponential Models To Data
Problem 3TI: Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to...
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A more refined model of measuring a population of bacteria or cancer cells is the logistic growth model. In this model, dN dt = rN(1 − N/K) , where r and K are constants called the intrinsic growth rate and carrying capacity. The carrying capacity is a measure of limited resources such as food and physical space provided by the environment. This model can also be applied in studying chemical reaction rates and the spread of disease. Any function N(t) = (K)/(1 + (K−N0 )/N0)e-rt , with N0 a nonzero initial population satisfies the logistic model.
Verify that N(0) = N0
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