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Salsk061 [2.6K]
3 years ago
7

Which term best describes the angle below

Mathematics
2 answers:
Sergio [31]3 years ago
8 0
Assuming that the angle is shown and the degrees is explicitly shown, then you can conclude the following:

If the angle >= 0 and the angle < 90, then the angle is an acute angle.
If the angle = 90, then the angle is a right angle.
If the angle > 90 and the angle <180, then the angle is an obtuse angle.
If the angle = 180, then the angle is a straight angle.
Kaylis [27]3 years ago
3 0
This is the angle, right? It is Acute.

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This is a GCSE maths question which i don’t understand.
Tpy6a [65]

Answer:

15

Step-by-step explanation:

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4 years ago
|5x|-2=18 helps love this problem please help
drek231 [11]

Answer:

x = 4

Step-by-step explanation:

The absolute value of 5x is still 5x.

5x - 2 = 18

Add 2 to both sides

5x = 20

Divide both sides by 5

x = 4

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4 years ago
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Which of the following relations is a function? A. (0, 4), (-2, 6), (0, 3), (-7, 2) B. (8, 1), (-2, 4), (0, 1), (8, 2) C. (0, 4)
fomenos

Answer: C

Step-by-step explanation:

C is a function because each of the inputs are distinct, meaning they only have one output each.

The other choices are not functions because at least one of the inputs corresponds to 2 or more outputs.

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2 years ago
The Insurance Institute reports that the mean amount of life insurance per household in the US is $110,000. This follows a norma
nata0808 [166]

Answer:

a) \sigma_{\bar X} = \frac{\sigma}{\sqrt{n}}= \frac{40000}{\sqrt{50}}= 5656.85

b) Since the distribution for X is normal then we know that the distribution for the sample mean \bar X is given by:

\bar X \sim N(\mu, \frac{\sigma}{\sqrt{n}})

c) P( \bar X >112000) = P(Z>\frac{112000-110000}{\frac{40000}{\sqrt{50}}}) = P(Z>0.354)

And we can use the complement rule and we got:

P(Z>0.354) = 1-P(Z

d) P( \bar X >100000) = P(Z>\frac{100000-110000}{\frac{40000}{\sqrt{50}}}) = P(Z>-1.768)

And we can use the complement rule and we got:

P(Z>-1.768) = 1-P(Z

e) P(100000< \bar X

And we can use the complement rule and we got:

P(-1.768

Step-by-step explanation:

a. If we select a random sample of 50 households, what is the standard error of the mean?

Previous concepts

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".  

Let X the random variable that represent the amount of life insurance of a population, and for this case we know the distribution for X is given by:

X \sim N(110000,40000)  

Where \mu=110000 and \sigma=40000

If we select a sample size of n =35 the standard error is given by:

\sigma_{\bar X} = \frac{\sigma}{\sqrt{n}}= \frac{40000}{\sqrt{50}}= 5656.85

b. What is the expected shape of the distribution of the sample mean?

Since the distribution for X is normal then we know that the distribution for the sample mean \bar X is given by:

\bar X \sim N(\mu, \frac{\sigma}{\sqrt{n}})

c. What is the likelihood of selecting a sample with a mean of at least $112,000?

For this case we want this probability:

P(X > 112000)

And we can use the z score given by:

z= \frac{\bar X  -\mu}{\frac{\sigma}{\sqrt{n}}}

And replacing we got:

P( \bar X >112000) = P(Z>\frac{112000-110000}{\frac{40000}{\sqrt{50}}}) = P(Z>0.354)

And we can use the complement rule and we got:

P(Z>0.354) = 1-P(Z

d. What is the likelihood of selecting a sample with a mean of more than $100,000?

For this case we want this probability:

P(X > 100000)

And we can use the z score given by:

z= \frac{\bar X  -\mu}{\frac{\sigma}{\sqrt{n}}}

And replacing we got:

P( \bar X >100000) = P(Z>\frac{100000-110000}{\frac{40000}{\sqrt{50}}}) = P(Z>-1.768)

And we can use the complement rule and we got:

P(Z>-1.768) = 1-P(Z

e. Find the likelihood of selecting a sample with a mean of more than $100,000 but less than $112,000

For this case we want this probability:

P(100000

And we can use the z score given by:

z= \frac{\bar X  -\mu}{\frac{\sigma}{\sqrt{n}}}

And replacing we got:

P(100000< \bar X

And we can use the complement rule and we got:

P(-1.768

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13 apples for 2 pies
Lady_Fox [76]
Each pie gets 13/2 apples=6.5 apples per pie
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