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natulia [17]
1 year ago
9

The angle θ1\theta_1 θ 1 ​ theta, start subscript, 1, end subscript is located in Quadrant II\text{II} II start text, I, I, end

text , and cos⁡(θ1)=−211\cos(\theta_1)=-\dfrac{2}{11} cos(θ 1 ​ )=− 11 2 ​ cosine, left parenthesis, theta, start subscript, 1, end subscript, right parenthesis, equals, minus, start fraction, 2, divided by, 11, end fraction . What is the value of sin⁡(θ1)\sin(\theta_1) sin(θ 1 ​ ) sine, left parenthesis, theta, start subscript, 1, end subscript, right parenthesis ?
Mathematics
1 answer:
melomori [17]1 year ago
6 0

Answer:

\dfrac{3\sqrt{13}}{11}

Step-by-step explanation:

Given that the angle \theta_1  is located in Quadrant II; and

\cos(\theta_1)=-\dfrac{2}{11}

In Quadrant II, x is negative and y is positive.

\cos(\theta)=\dfrac{Adjacent}{Hypotenuse},\sin(\theta)=\dfrac{Opposite}{Hypotenuse}\\$Adjacent=-2\\Hypotenuse=11\\

To find \sin(\theta_1), we first determine the opposite angle of \theta_1.

This will be done using the Pythagoras theorem.

Hypotenuse^2=Opposite^2+Adjacent^2\\11^2=Opposite^2+(-2)^2\\Opposite^2=121-4=117\\Opposite=\sqrt{117}=3\sqrt{13}

Therefore:

\sin(\theta_1)=\dfrac{Opposite}{Hypotenuse}=\dfrac{3\sqrt{13}}{11}

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Answer:

Y will arrive earlier than X one fourth of times.

Step-by-step explanation:

To solve this, we might notice that given that both events are independent of each other, the joint probability density function is the product of X and Y's probability density functions. For an uniformly distributed density function, we have that:

f_X(x) = \frac{1}{L}

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Now, as  X is distributed over a 1 hour interval, and Y is distributed over a 0.5 hour interval, we have:

f_X(x) = 1\\\\f_Y(y)=2.

Now, the probability of an event is equal to the integral of the density probability function:

\iint_A f_{X,Y} (x,y) dx\, dy

Where A is the in which the event happens, in this case, the region in which Y<X (Y arrives before X)

It's useful to draw a diagram here, I have attached one in which you can see the integration region.

You can see there a box, that represents all possible outcomes for Y and X. There's a diagonal coming from the box's upper right corner, that diagonal represents the cases in which both X and Y arrive at the same time, under that line we have that Y arrives before X, that is our integration region.

Let's set up the integration:

\iint_A f_{X,Y} (x,y) dx\, dy\\\\\iint_A f_{X} (x) \, f_{Y} (y) dx\, dy\\\\2 \iint_A  dx\, dy

We have used here both the independence of the events and the uniformity of distributions, we take the 2 out because it's just a constant and now we just need to integrate. But the function we are integrating is just a 1! So we can take the integral as just the area of the integration region. From the diagram we can see that the region is a triangle of height 0.5 and base 0.5. thus the integral becomes:

2 \iint_A  dx\, dy= 2 \times \frac{0.5 \times 0.5 }{2} \\\\2 \iint_A  dx\, dy= \frac{1}{4}

That means that one in four times Y will arrive earlier than X. This result can also be seen clearly on the diagram, where we can see that the triangle is a fourth of the rectangle.

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Answer:

a) ME=2.58 \sqrt{\frac{0.413(1-0.413)}{900}}=0.0423

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Step-by-step explanation:

1) Data given and notation  

n=900 represent the random sample taken    

X=372 represent the students were pursuing liberal arts degrees

\hat p=\frac{372}{900}=0.413 estimated proportion of students were pursuing liberal arts degrees

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z would represent the statistic (variable of interest)    

p_v represent the p value (variable of interest)    

p= population proportion of students were pursuing liberal arts degrees

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We are confident (99%) that about 37.1% to 45.5% of students were pursuing liberal arts degrees.

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