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SCORPION-xisa [38]
2 years ago
7

4400 dollars is placed in an account with an annual interest rate of 7.5%. To the nearest tenth of a year, how long will it take

for the account value to reach 33800 dollars?
Mathematics
2 answers:
gogolik [260]2 years ago
7 0

Answer: it take 28.5 years for the account value to reach 33800 dollars

Step-by-step explanation:

We would assume that the interest was compounded annually. The formula for determining compound interest is expressed as

A = P(1+r/n)^nt

Where

A = total amount in the account at the end of t years

r represents the interest rate.

n represents the periodic interval at which it was compounded.

P represents the principal or initial amount deposited

From the information given,

P = $4400

A = $33800

r = 7.5% = 7.5/100 = 0.075

n = 1 because it was compounded once in a year.

Therefore,

33800 = 4400(1 + 0.075/1)^1 × t

33800/4400 = (1 + 0.075)^t

7.68 = (1.075)^t

Taking log of both sides, it becomes

Log 7.68 = t log 1.075

0.885 = 0.031t

t = 0.885/0.031

t = 28.5 years

Katarina [22]2 years ago
6 0

Answer:

Step-by-step explanation:

The equation for the amount of money in an account after a certain amount is deposited and compounded after t years once per year is

A(t)=P(1+r)^t

Our A(t) = 33800, P = 4400, r = .075 and we are looking for t.  Filling in:

33800=4400(1+.075)^t and

33800=4400(1.075)^t

Begin by dividing both sides by 4400 to get

7.681818182=1.075^t

The only way to move that t our from its current position as an exponent is to take the natural log of both sides and follow the rules for natural logs:

ln(7.6181818182=ln(1.075)^t

The power rule of natural logs says we can move that exponent down in front, giving us:

ln(7.681818182)=t*ln(1.075)

Divide both sides by ln(1.075) to get

\frac{ln(7.61818182)}{ln(1.075)} =t

Do this division on your calculator to get

t = 28.2 years

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A sample of 1714 cultures from individuals in Florida diagnosed with a strep infection was tested for resistance to the antibiot
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Answer:

a) p represent the real population proportion of people who showed partial or complete resistance to the antibiotic

b) \hat p=\frac{973}{1714}=0.568 represent the estimated proportion of people who showed partial or complete resistance to the antibiotic

c) We are confident (95%) that the true proportion of individuals in Florida diagnosed with a strep infection was tested for resistance to the antibiotic penicillin present partial or complete resistance to the antibiotic is between 54.5% to 59.1%.  

Step-by-step explanation:

A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval".

The margin of error is the range of values below and above the sample statistic in a confidence interval.

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

Part a

Description in words of the parameter p

p represent the real population proportion of people who showed partial or complete resistance to the antibiotic

\hat p represent the estimated proportion of people who showed partial or complete resistance to the antibiotic

n=1714 is the sample size required

z_{\alpha/2} represent the critical value for the margin of error

The population proportion have the following distribution  

p \sim N(p,\sqrt{\frac{p(1-p)}{n}})

Part b

Numerical estimate for p

In order to estimate a proportion we use this formula:

\hat p =\frac{X}{n} where X represent the number of people with a characteristic and n the total sample size selected.

\hat p=\frac{973}{1714}=0.568 represent the estimated proportion of people who showed partial or complete resistance to the antibiotic

Part c

The confidence interval for a proportion is given by this formula

\hat p \pm z_{\alpha/2} \sqrt{\frac{\hat p(1-\hat p)}{n}}

For the 95% confidence interval the value of \alpha=1-0.95=0.05 and \alpha/2=0.025, with that value we can find the quantile required for the interval in the normal standard distribution.

z_{\alpha/2}=1.96

And replacing into the confidence interval formula we got:

0.568 - 1.96 \sqrt{\frac{0.568(1-0.568)}{1714}}=0.545

0.568 + 1.96 \sqrt{\frac{0.56(1-0.56)}{1714}}=0.591

And the 95% confidence interval would be given (0.545;0.591).

We are confident that about 54.5% to 59.1% of individuals in Florida diagnosed with a strep infection was tested for resistance to the antibiotic penicillin present partial or complete resistance to the antibiotic.  

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