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Novay_Z [31]
3 years ago
12

Kristen invests $5,745 in a bank. The bank pays 6.5% interest compounded monthly. How long must she leave the money in the bank

for it to double? Round the nearest tenth of a year.
Mathematics
1 answer:
s344n2d4d5 [400]3 years ago
3 0

formula is A=P(1-\frac{r}{n})^{nt}

where A=final amount

P=principal

r=interest rate in decimal

n=number of times per year it is compounded

t=time in years


we want to find where

A=2P

and P=5745

and r=6.5%=0.065

n=monthly=12


remember that ln(x^a)=a(ln(x))

also that (a^b)^c=a^{bc}

2(5745)=5745(1+\frac{0.065}{12})^{12t}, solving for t

divide both sides by 5745 to simplify things a bit

2=(1+\frac{0.065}{12})^{12t} I'd rather not simplify this because it give us a decimals and those aren't exact, if we combine, we get 12.065/12 for inside parenthases

2=(\frac{12.065}{12})^{12t}

take ln of both sides

ln(2)=ln((\frac{12.065}{12})^{12t})

ln(2)=(12t)ln(\frac{12.065}{12})

divide both sides by 12ln(\frac{12.065}{12})

\frac{ln(2)}{12ln(\frac{12.065}{12})}=t

using our calculator, t≈10.6927


so rounded, we get 10.7 years

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Janet is three years older than her sister julie. Janet’s brother is eight years younger than their sister Julie. The sum of all
SOVA2 [1]

Answer:

Julie is 20

Janet is 23

Their brother is 12

Step-by-step explanation:

20+23+12=43+12=55

8 0
3 years ago
What is the difference between Delta x and dx? ...?
MA_775_DIABLO [31]

Δx (delta x) is about a secant line, a line between two points representing the rate of change between those two points. That's a "differential" (between the two points).

dx is about a tangent line to one point, representing an instantaneous rate of change. That makes it a "derivative."

6 0
3 years ago
How do I do this problem?
Elenna [48]
Roots can be written as fraction exponents. An exponent of 1/2 means the square root.

(12 x^{4})^{1/2} =  \sqrt{12 x^{4} }  \\  \\ \sqrt{12 x^{4} } =  \sqrt{3*4*x^{2}*x^{2}} = 2x^{2} \sqrt{3}
8 0
3 years ago
Describe how the range of a data set can help describe its variability.
katovenus [111]

Answer:

The range is defined as the difference between the term with the highest value and the term with the lowest value. This statistic is used to measure the variability of a series of data because it provides information on how far apart the values of a tail of the distribution are from the values at the other end of the tail.

Imagine that you manufacture a type of spare part for cars that must have a measurement of 10 cm with a margin of error of 1 cm.

This is:

10 ± 1 cm

Then you expect your manufacturing process to produce pieces with identical dimensions, that is, with little variability.

If you randomly select a sample of n pieces and measure them, the variability is expected to be low, so that your process is of quality, then expect a low range preferably less than 1 cm.

{10, 10.1, 10.5, 9.8, 9,6, 10.2} Range= 10.5 - 9.6 = 0.9 cm <em> low variability</em>

But if you find that the range is up to 8 cm, this would mean that not all pieces measure around 10 cm, it means that the variability of the measurements is high.

{14, 12, 11, 8, 7, 11, 12, 15} Range = 15 - 7 = 8 cm   <em>high variability </em>

6 0
3 years ago
Read 2 more answers
National data indicates that​ 35% of households own a desktop computer. In a random sample of 570​ households, 40% owned a deskt
Elan Coil [88]

Answer:

Yes, this provide enough evidence to show a difference in the proportion of households that own a​ desktop.

Step-by-step explanation:

We are given that National data indicates that​ 35% of households own a desktop computer.

In a random sample of 570​ households, 40% owned a desktop computer.

<em><u>Let p = population proportion of households who own a desktop computer</u></em>

SO, Null Hypothesis, H_0 : p = 25%   {means that 35% of households own a desktop computer}

Alternate Hypothesis, H_A : p \neq 25%   {means that % of households who own a desktop computer is different from 35%}

The test statistics that will be used here is <u>One-sample z proportion</u> <u>statistics</u>;

                                  T.S.  = \frac{\hat p-p}{{\sqrt{\frac{\hat p(1-\hat p)}{n} } } } }  ~ N(0,1)

where, \hat p = sample proportion of 570​ households who owned a desktop computer = 40%

            n = sample of households = 570

So, <u><em>test statistics</em></u>  =  \frac{0.40-0.35}{{\sqrt{\frac{0.40(1-0.40)}{570} } } } }

                               =  2.437

<em>Since, in the question we are not given with the level of significance at which to test out hypothesis so we assume it to be 5%. Now at 5% significance level, the z table gives critical values of -1.96 and 1.96 for two-tailed test. Since our test statistics doesn't lies within the range of critical values of z so we have sufficient evidence to reject our null hypothesis as it will fall in the rejection region due to which we reject our null hypothesis.</em>

Therefore, we conclude that % of households who own a desktop computer is different from 35%.

3 0
3 years ago
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