Consider two populations that can be modeled by the logistic equation withthe same carrying capacity, but with different values of k. Which populationapproaches the carrying capacity most quickly, the one with the smaller or largervalue of k? You may want to think geometrically (check out some slope fields),analytically (look at the form of the solution), or numinto the solution).erically (plug some t values

We are given two population modeled by logistic equations having same carrying capacity but…

Answered: Consider two populations that can be…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

See similar textbooks

Similar questions

Model the following data using an exponential function of the form f(x) = Ab". You need to do this rigorously, that is, set up a system of equations, and solve it to get A and b. Getting the right answer by guessing will earn no credit. (a) f(x) is exponential and goes through the points (1, 2) and (4,6). (b) f(x) is exponential and goes through the points (2, 75) and (5, 9375).
Assume there is a certain population of fish in a pond whose growth is described by the logistic equation. It is estimated that the carrying capacity for the pond is 1000 fish. Absent constraints, the population would grow by 190% per year.If the starting population is given by �0=300, then after one breeding season the population of the pond is given by�1 = After two breeding seasons the population of the pond is given by�2 =
Table 4.18 shows estimated effects for a fitted logistic regression model with squamous cell esophageal cancer (1 = yes, 0 = no) as the response variable Y. Smoking status (S) equals 1 for at least one pack per day and 0 other- wise, alcohol consumption (A) equals the average number of alcoholic drinks consumed per day, and race (R) equals 1 for blacks and 0 for whites. A. To describe the race-by-smoking interaction, construct the prediction equation when R = 1 and again when R = 0. Find the fitted YS conditional odds ratio for each case. Similarly, construct the prediction equation when S = 1 and again when S = 0. Find the fitted YR conditional odds ratio for each case. Note that, for each association, the coefficient of the cross-product term is the difference between the log odds ratios at the two fixed levels for the other variable. B. In Table 4.18, explain what the coefficients of R and S represent, for the coding as given above. What hypotheses do the P -values refer to for…
a) Logistically, the growth of Mrs. Fields cookies in different states is closely modeled after this: 19440 P(t) = 1 + 485 e -0.4444t P(t) is number of U.S. cities with a Mrs. Fields cookie storet years after the year 2000, and t is time in years after the year 2000. Use this logistic model to find the number of cities that had a Mrs. Fields cookie store in the year 2000, when they first opened. U.S. cities in the year 2000. b) How many U.S. cities had a Mrs. Fields cookie store in the year 2015. (round to the nearest whole number) U.S. cities in the year 2015.
answer a-d (manual computation)
How does the discrete logistic growth model (Ricker) vary from that of deterministic form? Are there differences in the predictions as the input parameters change? K= 300 r= 0.5 N= 5 Time= 50
Hanny
Please please answer both a and b Thank you so much
Please answer the 3 questions below

Recommended textbooks for you

Advanced Engineering Mathematics

Advanced Math

ISBN:

9780470458365

Author:

Erwin Kreyszig

Publisher:

Wiley, John & Sons, Incorporated

Numerical Methods for Engineers

Advanced Math

ISBN:

9780073397924

Author:

Steven C. Chapra Dr., Raymond P. Canale

Publisher:

McGraw-Hill Education

Introductory Mathematics for Engineering Applicat…

Advanced Math

ISBN:

9781118141809

Author:

Nathan Klingbeil

Publisher:

WILEY

Advanced Engineering Mathematics

Advanced Math

ISBN:

9780470458365

Author:

Erwin Kreyszig

Publisher:

Wiley, John & Sons, Incorporated

Numerical Methods for Engineers

Advanced Math

ISBN:

9780073397924

Author:

Steven C. Chapra Dr., Raymond P. Canale

Publisher:

McGraw-Hill Education

Introductory Mathematics for Engineering Applicat…

Advanced Math

ISBN:

9781118141809

Author:

Nathan Klingbeil

Publisher:

WILEY

Mathematics For Machine Technology

Advanced Math

ISBN:

9781337798310

Author:

Peterson, John.

Publisher:

Cengage Learning,

Basic Technical Mathematics

Advanced Math

ISBN:

9780134437705

Author:

Washington

Publisher:

PEARSON

Topology

Advanced Math

ISBN:

9780134689517

Author:

Munkres, James R.

Publisher:

Pearson,

SEE MORE TEXTBOOKS