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Ilya [14]
3 years ago
15

A line segment has endpoints P (3, 6) and Q (12, 18) and is dilated so that its new endpoints are P’ (2, 4) and Q’ (8, 12). What

is the scale factor? If the length of PQ is 15, what is the length of P’Q’?
Show all work.
Mathematics
2 answers:
just olya [345]3 years ago
7 0

Answer:

Scale Factor ≈ 0.67

P'Q' Length = 10

Step-by-step explanation:

To find the scale factor, a relationship must be found between the original points, and the dilated points. To do this, simply divide the new points by the old points.

P to P' : \frac{2}{3}=0.6667 AND \frac{4}{6}=0.6667

Q to Q' : \frac{8}{12}=0.6667 AND \frac{12}{18}=0.6667

Therefore, the scale factor is 0.6667 ≈ 0.67

The length of P'Q' can be calculated with the distance formula:

d^{2}=(y_{1}-y_{2} )^{2} +(x_{1}-x_{2} )^{2} \\d^{2} =(4-12)^{2} + (2-8)^{2} \\d^{2} =(-8)^{2} +(-6)^{2} \\d^{2} =64+36\\d=\sqrt{100} =10

Alternatively, you could multiply the length of PQ with the scale factor to find P'Q':

15*0.6667=10

Fed [463]3 years ago
4 0
It should be 14, because 8 - 2 = 6 and 12 - 4 = 8
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Step-by-step explanation:

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s_2=\sqrt{\dfrac{1}{10}\cdot [(-1-(-0.273))^2+(12-(-0.273))^2+...+(-3-(-0.273))^2]}\\\\\\

s_2=\sqrt{\dfrac{1}{10}\cdot [(0.53)+(150.62)+...+(115.07)+(0.53)+(7.44)]}\\\\\\s_2=\sqrt{\dfrac{348.182}{10}}=\sqrt{34.82}\\\\\\s_2=5.901

a) We have to calculate a 95% confidence interval for the difference between means, with a T-model.

The Group 1, of size n1=10 has a mean of 5 and a standard deviation of 8.743.

The Group 2, of size n2=11 has a mean of -0.273 and a standard deviation of 5.901.

The difference between sample means is Md=5.273.

M_d=M_1-M_2=5-(-0.273)=5.273

The estimated standard error of the difference between means is computed using the formula:

s_{M_d}=\sqrt{\dfrac{\sigma_1^2}{n_1}+\dfrac{\sigma_2^2}{n_2}}=\sqrt{\dfrac{8.743^2}{10}+\dfrac{5.901^2}{11}}\\\\\\s_{M_d}=\sqrt{7.644+3.166}=\sqrt{10.81}=3.288

The degrees of freedom for this test are:

df=n_1+n_2-1=10+11-2=19

The critical t-value for a 95% confidence interval and 19 degrees of freedom is t=1.96.

The margin of error (MOE) can be calculated as:

MOE=t\cdot s_{M_d}=1.96 \cdot 3.288=6.444

Then, the lower and upper bounds of the confidence interval are:

LL=M_d-t \cdot s_{M_d} = 5.273-6.444=-1.171\\\\UL=M_d+t \cdot s_{M_d} = 5.273+6.444=11.717

The 95% confidence interval for the mean is (-1.171, 11.717).

b) This is a hypothesis test for the difference between populations means.

The claim is that increasing the amount of calcium in our diet reduce blood pressure.

Then, the null and alternative hypothesis are:

H_0: \mu_1-\mu_2=0\\\\H_a:\mu_1-\mu_2> 0

The significance level is 0.05.

The sample 1, of size n1=10 has a mean of 5 and a standard deviation of 8.743.

The sample 1, of size n1=11 has a mean of -0.273 and a standard deviation of 5.901.

The difference between sample means is Md=5.273.

M_d=M_1-M_2=5-(-0.273)=5.273

The estimated standard error of the difference between means is computed using the formula:

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Then, we can calculate the t-statistic as:

t=\dfrac{M_d-(\mu_1-\mu_2)}{s_{M_d}}=\dfrac{5.273-0}{3.288}=\dfrac{5.273}{3.288}=1.604

The degrees of freedom for this test are:

df=n_1+n_2-1=10+11-2=19

This test is a right-tailed test, with 19 degrees of freedom and t=1.604, so the P-value for this test is calculated as (using a t-table):

P-value=P(t>1.604)=0.063

As the P-value (0.063) is bigger than the significance level (0.05), the effect is not significant.

The null hypothesis failed to be rejected.

There is not enough evidence to support the claim that increasing the amount of calcium in our diet reduce blood pressure.

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