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jonny [76]
3 years ago
8

The perimeter of a rectangle is represented by 4x^2+5x-2. The perimeter of a smaller rectangle is represented by x^2+3x+5. Which

polynomial expression represents how much larger the first rectangle is than the smaller rectangle ?
PLease help !!!!

Mathematics
1 answer:
crimeas [40]3 years ago
4 0

a is correct

Step-by-step explanation:

Area of Bigger rectangle = 4x2 + 5x - 2

Area of Smaller rectangle = x2 + 3× + 5

diff. = ( 4x2 + 5x - 2) - (x2 + 3x - 5)

= 4x2 + 5x -2-x2 - 3x - 5

= 3x2 + 2x - 7

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Answer:

a) P(0.11

And we can find this probability with this difference and with the normal standard table or excel:

P(-1.11

b) P(0.11 < \bar X < 0.13)

And we can use the z score defined by:

z = \frac{\bar X -\mu}{\frac{\sigma}{\sqrt{n}}}

And using the limits we got:

z = \frac{0.11-0.12}{\frac{0.009}{\sqrt{4}}}= -2.22

z = \frac{0.13-0.12}{\frac{0.009}{\sqrt{4}}}= 2.22

And we want to find this probability:

P(-2.22< Z

Step-by-step explanation:

Previous concepts

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".

The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".  

Part a

Let X the random variable that represent the resitances of a population, and for this case we know the distribution for X is given by:

X \sim N(0.12,0.009)  

Where \mu=0.12 and \sigma=0.009

We are interested on this probability

P(0.11

And the best way to solve this problem is using the normal standard distribution and the z score given by:

z=\frac{x-\mu}{\sigma}

If we apply this formula to our probability we got this:

P(0.11

And we can find this probability with this difference and with the normal standard table or excel:

P(-1.11

Part b

We select a sample size of n =4. And since the distribution for X is normal then we know that the distribution for the sample mean \bar X is given by:

\bar X \sim N(\mu, \frac{\sigma}{\sqrt{n}})

And we want this probability:

P(0.11 < \bar X < 0.13)

And we can use the z score defined by:

z = \frac{\bar X -\mu}{\frac{\sigma}{\sqrt{n}}}

And using the limits we got:

z = \frac{0.11-0.12}{\frac{0.009}{\sqrt{4}}}= -2.22

z = \frac{0.13-0.12}{\frac{0.009}{\sqrt{4}}}= 2.22

And we want to find this probability:

P(-2.22< Z

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