A biologist is researching a newly discovered species of bacteria. At time t=0, he puts 250 bacteria into what he has determined to be a favorable growth. Eight hours later, he messages 750 bacteria. This can be modeled by the equation y=ae^kt , where a is the initial amount of bacteria. A. Find the rate of growth, k, of bacteria, then determine the equation that models this situation B. How many bacteria are present at time t=12 C. At what time will the number of bacteria reach 2500
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
A biologist is researching a newly discovered species of bacteria. At time t=0, he puts 250 bacteria into what he has determined to be a favorable growth. Eight hours later, he messages 750 bacteria. This can be modeled by the equation y=ae^kt , where a is the initial amount of bacteria.
A. Find the rate of growth, k, of bacteria, then determine the equation that models this situation
B. How many bacteria are present at time t=12
C. At what time will the number of bacteria reach 2500
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