Use the function p(t)=poekt, where p(t)=population at time t, p0= the initial population, and k is the growth or decay rate. Scenario: A scientist is studying bacteria in a favorable growth medium. The population is growing exponentially. The scientist measures a bacteria population of 850, then 2 hours later measures a bacteria population of 925. a. Find the k-value for the scenario. Round to the nearest ten-thousandths. b. Use the k-value found in part a and the initial population of 850 and write the function that models the population growth in the scenario. c. Use the function created in part b. to predict the bacteria population after 24 hours.
Use the function p(t)=poekt, where p(t)=population at time t, p0= the initial population, and k is the growth or decay rate. Scenario: A scientist is studying bacteria in a favorable growth medium. The population is growing exponentially. The scientist measures a bacteria population of 850, then 2 hours later measures a bacteria population of 925. a. Find the k-value for the scenario. Round to the nearest ten-thousandths. b. Use the k-value found in part a and the initial population of 850 and write the function that models the population growth in the scenario. c. Use the function created in part b. to predict the bacteria population after 24 hours.
Chapter5: Exponential And Logarithmic Functions
Section5.5: Exponential And Logarithmic Models
Problem 30E: The table shows the mid-year populations (in millions) of five countries in 2015 and the projected...
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Use the function p(t)=poekt, where p(t)=population at time t, p0= the initial population, and k is the growth or decay rate.
Scenario: A scientist is studying bacteria in a favorable growth medium. The population is growing exponentially. The scientist measures a bacteria population of 850, then 2 hours later measures a bacteria population of 925.
a. Find the k-value for the scenario. Round to the nearest ten-thousandths.
b. Use the k-value found in part a and the initial population of 850 and write the function that models the population growth in the scenario.
c. Use the function created in part b. to predict the bacteria population after 24 hours.
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