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julsineya [31]
3 years ago
9

Bacteria can multiply at an alarming rate when each bacteria splits into two new cells, thus doubling. If we start with only one

bacteria which can double every hour, how many bacteria will we have by the end of one day? Show your work.
Mathematics
1 answer:
Yuliya22 [10]3 years ago
4 0

Answer:

y = a(b)^t

Where a =1 represent the initial amount of bacteria and b =2 represent the growth factor, for this case since each hour we double the number of bacteria for this reason b =2. And t represent the number of hours after the first bacteria is founded.

So then our model would be given by:

y = 1 (2)^t

And since we want to find the number of bacteria at the end of one day, and we know that one day = 24 hours we can replace the value of t =24 into the model and we got:

f(24) = 1 (2)^{24}=16777216

Then we can conclude that at the end of the day we would expect 16777216 bacteria

Step-by-step explanation:

For this case we can use the exponential model given by this general expression:

y = a(b)^t

Where a =1 represent the initial amount of bacteria and b =2 represent the growth factor, for this case since each hour we double the number of bacteria for this reason b =2. And t represent the number of hours after the first bacteria is founded.

So then our model would be given by:

y = 1 (2)^t

And since we want to find the number of bacteria at the end of one day, and we know that one day = 24 hours we can replace the value of t =24 into the model and we got:

f(24) = 1 (2)^{24}=16777216

Then we can conclude that at the end of the day we would expect 16777216 bacteria

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Answer:

P(X \geq 1) = 1-P(X

And we can find the individual probability like this:

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And replacing we got:

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Step-by-step explanation:

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Previous concepts  

The binomial distribution is a "DISCRETE probability distribution that summarizes the probability that a value will take one of two independent values under a given set of parameters. The assumptions for the binomial distribution are that there is only one outcome for each trial, each trial has the same probability of success, and each trial is mutually exclusive, or independent of each other".  

Solution to the problem

Let X the random variable of interest, on this case we now that:  

X \sim Binom(n=16, p=0.5)  

The probability mass function for the Binomial distribution is given as:  

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Where (nCx) means combinatory and it's given by this formula:  

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