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ki77a [65]
3 years ago
11

An artist used this design to create a stained glass window. If m∠M = 48° and

Mathematics
1 answer:
e-lub [12.9K]3 years ago
4 0

Answer:

m\angle LKM=36^o

Step-by-step explanation:

The picture of the question in the attached figure

step 1

Find the measure of arc KN

we know that

The inscribed angle is half that of the arc comprising

so

m\angle M=\frac{1}{2}(arc\ KN)

we have

m\angle M=48^o

substitute

48^o=\frac{1}{2}(arc\ KN)

arc\ KN=96^o

step 2

Find the measure of arc LM

we know that

arc\ KN=arc\ MN=arc\ KL=96^o

so

3arc\ KN+arc\ LM=360^o ----> by complete circle

substitute given value

3(96^o)+arc\ LM=360^o

arc\ LM=360^o-288^o=72^o

step 3

Find the measure of angle LKM

we know that

The inscribed angle is half that of the arc comprising

so

m\angle LKM=\frac{1}{2}(arc\ LM)

substitute the given value

m\angle LKM=\frac{1}{2}(72^o)=36^o

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a) y=-0.317 x +46.02

b) Figure attached

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Step-by-step explanation:

We assume that th data is this one:

x: 30, 30, 30, 50, 50, 50, 70,70, 70,90,90,90

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S_{xx}=\sum_{i=1}^n x^2_i -\frac{(\sum_{i=1}^n x_i)^2}{n}

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\sum_{i=1}^n x_i = 30+30+30+50+50+50+70+70+70+90+90+90=720

\sum_{i=1}^n y_i =38+43+29+32+26+33+19+27+23+14+19+21=324

\sum_{i=1}^n x^2_i =30^2+30^2+30^2+50^2+50^2+50^2+70^2+70^2+70^2+90^2+90^2+90^2=49200

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\sum_{i=1}^n x_i y_i =30*38+30*43+30*29+50*32+50*26+50*33+70*19+70*27+70*23+90*14+90*19+90*21=17540

With these we can find the sums:

S_{xx}=\sum_{i=1}^n x^2_i -\frac{(\sum_{i=1}^n x_i)^2}{n}=49200-\frac{720^2}{12}=6000

S_{xy}=\sum_{i=1}^n x_i y_i -\frac{(\sum_{i=1}^n x_i)(\sum_{i=1}^n y_i)}=17540-\frac{720*324}{12}{12}=-1900

And the slope would be:

m=-\frac{1900}{6000}=-0.317

Nowe we can find the means for x and y like this:

\bar x= \frac{\sum x_i}{n}=\frac{720}{12}=60

\bar y= \frac{\sum y_i}{n}=\frac{324}{12}=27

And we can find the intercept using this:

b=\bar y -m \bar x=27-(-0.317*60)=46.02

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For this case we can use excel and we got the figure attached as the result.

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In oder to calculate S^2 we need to calculate the MSE, or the mean square error. And is given by this formula:

MSE=\frac{SSE}{df_{E}}

The degred of freedom for the error are given by:

df_{E}=n-2=12-2=10

We can calculate:

S_{y}=\sum_{i=1}^n y^2_i -\frac{(\sum_{i=1}^n y_i)^2}{n}=9540-\frac{324^2}{12}=792

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SSR=\frac{S^2_{xy}}{S_{xx}}=\frac{(-1900)^2}{6000}=601.67

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So then :

S^2=\hat \sigma^2=MSE=\frac{190.33}{10}=19.03

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