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SashulF [63]
3 years ago
15

Which function has a range of {y|y<_5}?

Mathematics
1 answer:
Sveta_85 [38]3 years ago
8 0

Answer:

f(x) = -(x-4)² + 5

Step-by-step explanation:

f(x) = -(x-4)² + 5

Has a maximum vertex at (4,5)

Which means the function has a greatest value of 5 at x = 4

Therefore the range is:

y《5

You might be interested in
Which translation maps the graph of the function f(x) = x2 onto the function g(x) = x2 + 2x + 6?
Veronika [31]

Answer:

left 1 unit, up 5 units

Step-by-step explanation:

First factor

g(x)=x^2+2x+6 = (x+1)^2+5

The standard transformation formula is

g(x) = a*f(bx-h) + k

which means

a=1, b=1,h=-1, k=5

or

h=-1 means translate left one unit

k=5 means translate up 5 units.  

Choose the first option: left 1 unit, up 5 units

3 0
3 years ago
Read 2 more answers
At a new exhibit in the Museum of Science, people are asked to choose between 94 or 220 random draws from a machine. The machine
Tresset [83]

Answer:

0.0869 = 8.69% probability of getting more than 61% green balls.

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal Probability Distribution:

Problems of normal distributions can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the z-score of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean \mu = p and standard deviation s = \sqrt{\frac{p(1-p)}{n}}

The machine is known to have 99 green balls and 78 red balls.

This means that p = \frac{99}{99+78} = 0.5593

Mean and standard deviation:

\mu = p = 0.5593

s = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.5593*0.4407}{99+78}} = 0.0373

a. Calculate the probability of getting more than 61% green balls.

This is 1 subtracted by the pvalue of Z when X = 0.61. So

Z = \frac{X - \mu}{\sigma}

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{0.61 - 0.5593}{0.0373}

Z = 1.36

Z = 1.36 has a pvalue of 0.9131

1 - 0.9131 = 0.0869

0.0869 = 8.69% probability of getting more than 61% green balls.

8 0
2 years ago
Please help me ASAP
miskamm [114]

Answer:

540 m so yaaaaàaaaaaaaaaaaaaaaa

6 0
2 years ago
Convert 0.0002 ug to mg:<br> Please help
Ksju [112]

1 ug = 0,001 mg

0,0002 ug= x

x= (0,0002×0,001)/1

x= 2e-7

8 0
3 years ago
Help me with math please, really urgent!
Alenkasestr [34]

X2 is on the right side, X1 is on the left side so -14 would be X1 and 2 would be x2

so it would be the first answer

7 0
3 years ago
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