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balandron [24]
3 years ago
15

If ƒ={(5, 1),(6, 2),(7, 3),(8, 1),(9, 7)}, then the range of ƒ is

Mathematics
2 answers:
yuradex [85]3 years ago
7 0
1,2,3,7
I believe the range is just depending on your y values,and since an equation is not given your range should just be the y values of that set
son4ous [18]3 years ago
3 0

I think this should help :-)

1. The points that are in given in the (x, y) form aka (x-coordinate, y-coordinate).

2. The range is the set of values onto which ƒ sends the x's.


The x's are sent the numbers 1, 2, 3, 1, 7 which ends up looking like {1,2, 3, 7}

So the answer is {1,2,3,7}

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See the ​attached file.
Masja [62]

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1)

f(4) = 4(4) - 4^2 = 16 - 16 = 0

f(-4) = 4(-4) - (-4)^2 = -16 - 16 = -32

f(4) - f(-4) = 0 - (-32) = 32

2)

f(3/2) = 4(3/2) - (3/2)^2

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√f(3/2) = √(15/4) = √15 / 2

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f(x + h) = 4(x + h) - (x + h)^2

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So

[f(x + h) -f(x - h) ] / 2h

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A random sample of 10 parking meters in a resort community showed the following incomes for a day. Assume the incomes are normal
GenaCL600 [577]

Answer:

A 95% confidence interval for the true mean is [$3.39, $6.01].

Step-by-step explanation:

We are given that a random sample of 10 parking meters in a resort community showed the following incomes for a day;

Incomes (X): $3.60, $4.50, $2.80, $6.30, $2.60, $5.20, $6.75, $4.25, $8.00, $3.00.

Firstly, the pivotal quantity for finding the confidence interval for the population mean is given by;

                         P.Q.  =  \frac{\bar X-\mu}{\frac{s}{\sqrt{n} } }  ~ t_n_-_1

where, \bar X = sample mean income = \frac{\sum X}{n} = $4.70

            s = sample standard deviation = \sqrt{\frac{\sum (X-\bar X)^{2} }{n-1} }  = $1.83

            n = sample of parking meters = 10

            \mu = population mean

<em>Here for constructing a 95% confidence interval we have used a One-sample t-test statistics because we don't know about population standard deviation.</em>

<u>So, 95% confidence interval for the population mean, </u>\mu<u> is ;</u>

P(-2.262 < t_9 < 2.262) = 0.95  {As the critical value of t at 9 degrees of

                                            freedom are -2.262 & 2.262 with P = 2.5%}  

P(-2.262 < \frac{\bar X-\mu}{\frac{s}{\sqrt{n} } } < 2.262) = 0.95

P( -2.262 \times {\frac{s}{\sqrt{n} } } < {\bar X-\mu < 2.262 \times {\frac{s}{\sqrt{n} } } ) = 0.95

P( \bar X-2.262 \times {\frac{s}{\sqrt{n} } } < \mu < \bar X+2.262 \times {\frac{s}{\sqrt{n} } } ) = 0.95

<u>95% confidence interval for</u> \mu = [ \bar X-2.262 \times {\frac{s}{\sqrt{n} } } , \bar X+2.262 \times {\frac{s}{\sqrt{n} } } ]

                                         = [ 4.70-2.262 \times {\frac{1.83}{\sqrt{10} } } , 4.70+ 2.262 \times {\frac{1.83}{\sqrt{10} } } ]

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Therefore, a 95% confidence interval for the true mean is [$3.39, $6.01].

The interpretation of the above result is that we are 95% confident that the true mean will lie between incomes of $3.39 and $6.01.

Also, the margin of error  =  2.262 \times {\frac{s}{\sqrt{n} } }

                                          =  2.262 \times {\frac{1.83}{\sqrt{10} } }  = <u>1.31</u>

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