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Elden [556K]
3 years ago
5

Convert r = 8cos θ to rectangular form.

Mathematics
1 answer:
nikklg [1K]3 years ago
6 0

Answer:

(x-4)^2+y^2=16

This is a circle with radius \sqrt{16}=4 and center (4,0).

Step-by-step explanation:

Recall the following:

x=r\cos(\theta)

y=r\sin(\theta)

\frac{y}{x}=\tan(\theta)

x^2+y^2=r^2

We are given r=8\cos(theta).

Multiply both sides by r:

r(r)=8\cos(\theta)r

Reorder on right and simplify on left:

r^2=8r\cos(theta)

We can now make some replacements from our "Recall" section:

x^2+y^2=8x

We can probably leave like this, but sometimes we are required to put in a more identifying form.

This is a circle. I'm going to write in the form (x-h)^2+(y-k)^2=r^2.

Subtract 8x on both sides:

x^2-8x+y^2=0

x^2-8x+\text{(blank)}+y^2=0+\text{(blank)}

We are going to fill those "blanks" in so that we can complete the square for the x part.

x^2-8x+(\frac{-8}{2})^2+y^2=0+(\frac{-8}{2})^2

(x+\frac{-8}{2})^2+y^2=0+(-4)^2

(x-4)^2+y^2=0+16

(x-4)^2+y^2=16

So our equation is that of a circle with radius \sqrt{16}=4 and center (4,0).

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Answer:

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\hat p_B= \frac{20}{120}=0.167

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\hat p_C= \frac{65}{300}=0.217

z=\frac{0.217-0.333}{\sqrt{\frac{0.333(1-0.333)}{300}}}\approx -4.17  

So then the best solution for this case would be:

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Step-by-step explanation:

Data given and notation

n represent the random sample taken

X represent the number of scissors selected for each friend

\hat p=\frac{X}{n} estimated proportion of  scissors selected for each friend

p_o=\frac{1}{3}=0.333 is the value that we want to test

\alpha represent the significance level

z would represent the statistic (variable of interest)

p_v represent the p value (variable of interest)  

Concepts and formulas to use  

We need to conduct a hypothesis in order to test the claim that the proportion that the friend will pick scissors is less than 1/3 or 0.333, the system of hypothesis would be:  

Null hypothesis:p\geq 0.333  

Alternative hypothesis:p < 0.333  

When we conduct a proportion test we need to use the z statistic, and the is given by:  

z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}} (1)  

The One-Sample Proportion Test is used to assess whether a population proportion \hat p is significantly different from a hypothesized value p_o.

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Since we have all the info requires we can replace in formula (1) like this:  

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z=\frac{0.217-0.333}{\sqrt{\frac{0.333(1-0.333)}{300}}}\approx -4.17  

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