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Bad White [126]
3 years ago
6

Can anybody help with this question

Mathematics
2 answers:
noname [10]3 years ago
8 0
You answer will be either 15% or 13%
prohojiy [21]3 years ago
5 0
I'm late but i think the answer is 13%
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Please answer this what is the answer to this question now
Tanya [424]

Answer:

19

Step-by-step explanation:

M is the center of the triangle, means that MR=MQ=PM

and M is the in center of the triangle=MS=MT=MU=19

8 0
3 years ago
Click on the numbers to enter the answers in the boxes.​
djyliett [7]

Answer:

957 - 249 = 708

The number that goes above the 5 is 4

Number above the 7 is 17

Step-by-step explanation:

7 0
3 years ago
Read 2 more answers
Which one is lower 31.54 for 2 hours or 43.96 for 3.5 hours
pychu [463]
The answer would be 43.96 for 3.5 hours because for each hour it's 12.56
7 0
3 years ago
Graph the system. Tell whether the system has one solution, no solution, or infinitely many solutions. y = –2x + 1 y = –2x – 3
Alchen [17]
Let's try the actual solution of the system

<span>y = –2x + 1
y = –2x – 3

Note that the slopes of the graphs of these two lines are the same:  -2.

That means that the lines are parallel to one another.

Only the y-intercepts (1 and -3) are different.

Since the 2 lines never intersect, the system has no solution.

</span>
8 0
3 years ago
A random variable X follows the uniform distribution with a lower limit of 670 and an upper limit of 750.a. Calculate the mean a
DENIUS [597]

You can compute both the mean and second moment directly using the density function; in this case, it's

f_X(x)=\begin{cases}\frac1{750-670}=\frac1{80}&\text{for }670\le x\le750\\0&\text{otherwise}\end{cases}

Then the mean (first moment) is

E[X]=\displaystyle\int_{-\infty}^\infty x\,f_X(x)\,\mathrm dx=\frac1{80}\int_{670}^{750}x\,\mathrm dx=710

and the second moment is

E[X^2]=\displaystyle\int_{-\infty}^\infty x^2\,f_X(x)\,\mathrm dx=\frac1{80}\int_{670}^{750}x^2\,\mathrm dx=\frac{1,513,900}3

The second moment is useful in finding the variance, which is given by

V[X]=E[(X-E[X])^2]=E[X^2]-E[X]^2=\dfrac{1,513,900}3-710^2=\dfrac{1600}3

You get the standard deviation by taking the square root of the variance, and so

\sqrt{V[X]}=\sqrt{\dfrac{1600}3}\approx23.09

8 0
3 years ago
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