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anyanavicka [17]
4 years ago
14

The bird population in Louisiana is decreasing at a rate of 15% per day due to the oil spill. If there are 12,000 birds today, h

ow many will there be three weeks from now?
Mathematics
1 answer:
tiny-mole [99]4 years ago
8 0
<h3>Answer: 395 birds</h3>

==============================================

Work Shown:

The formula to use is

A = P*(1+r)^x

where,

P = 12000 is the initial population

r = -0.15 represents the growth rate in decimal form; which is really a decay/decrease due to r being negative

x = 21 days have passed by (3 weeks = 3*7 = 21 days)

These values lead to...

A = P*(1+r)^x

A = 12000*(1+(-0.15))^21

A = 12000*(1-0.15)^21

A = 12000*(0.85)^21

A = 12000*0.03294560142183

A = 395.34721706196

A = 395

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Answer:

a) P(X=1)=(5C1)(0.25)^1 (1-0.25)^{5-1}=0.39551

b)  P(X \leq 1) = P(X=0) +P(X=1)=0.23730+0.39551 =0.63281

c) P(X \geq 2) = 1-P(X

And for this case we can use the result from part b

P(X \geq 2) = 1-P(X

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P(X \neq 1) = 1-P(X=1)= 1-0.39551=0.60449

Step-by-step explanation:

Previous concepts

A Bernoulli trial is "a random experiment with exactly two possible outcomes, "success" and "failure", in which the probability of success is the same every time the experiment is conducted". And this experiment is a particular case of the binomial experiment.

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".

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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Part a

For this case our random variable X who represent the "number among the five who use the express checkout." follows X \sim Bin (n=5, p=0.25)

And we can find P(X=1) replacing on the mass function like this:

P(X=1)=(5C1)(0.25)^1 (1-0.25)^{5-1}=0.39551

Part b

For this case assuming that we want to find this probability P(X \leq 1) we can do this:

P(X \leq 1) = P(X=0) +P(X=1)

P(X=0)=(5C0)(0.25)^0 (1-0.25)^{5-0}=0.23730

P(X=1)=(5C1)(0.25)^1 (1-0.25)^{5-1}=0.39551

P(X \leq 1) = P(X=0) +P(X=1)=0.23730+0.39551 =0.63281

Part c

We can find P(2 \leq X) replacing on the mass function like this, using the complement rule:

P(X \geq 2) = 1-P(X

And for this case we can use the result from part b

P(X \geq 2) = 1-P(X

Part d

Assuming that we want to find this probability:

P(X \neq 1) since the random variable just takes values between 0 and 5 we can use the complement rule like this:

P(X \neq 1) = 1-P(X=1)= 1-0.39551=0.60449

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