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steposvetlana [31]
2 years ago
7

Solve the following system of equations.

Mathematics
1 answer:
Andre45 [30]2 years ago
4 0
The answer is (5,-5)
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Helppppppppppppp meeee
lora16 [44]

A. I think the cordinate of the meeting place will be 11,11 and for B I don't even know why that's there..

C. I think it's 11 too. Idk but, when you check ur homework you can ask ur teacher/parent for help.

4 0
2 years ago
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Yesterday noah ran 2 1/2 miles in 3/5 hour. Emily ran 3 3/4 miles in 5/6 hour. Anna ran 3 1/2 miles in 3/4 hour how fast in mile
Dmitry_Shevchenko [17]

Answer:

Step-by-step explanation:

To calculate the speed of each one we proceed as follows:

speed=distance/time

a] Noah's speed:

distance=2.5 miles

time=3/5 hours

speed=(2 1/2)/(3/5)

=(5/2)/(3/5)

=5/2×5/3

=25/6

=4 1/6 mi/hr

Emily's speed

distance=3 3/4 miles

time=5/6 hour

thus

speed=(3 3/4)/(5/6)

=15/4)/(5/6)

=15/4×6/5

=4 1/2 mi/hr

Anna's speed:

distance=3 1/3 miles

time=3/5

speed=(3 1/3)/(3/5

=(10/3)/(3/5)

=10/3×5/3

=5 5/9 mi/hr

Anna was the fastest

6 0
2 years ago
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HURRY PLZ!!!!!! Which graph shows a negative correlation?
Anna [14]

Answer:

The answer is C

Step-by-step explanation:

did the test on edg

7 0
3 years ago
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Let U1, ..., Un be i.i.d. Unif(0, 1), and X = max(U1, ..., Un). What is the PDF of X? What is EX? Hint: Find the CDF of X first,
Kryger [21]

Answer:

E(X)= n \int_{0}^1 x^n dx = n [\frac{1}{n+1}- \frac{0}{n+1}]=\frac{n}{n+1}

Step-by-step explanation:

A uniform distribution, "sometimes also known as a rectangular distribution, is a distribution that has constant probability".

We need to take in count that our random variable just take values between 0 and 1 since is uniform distribution (0,1). The maximum of the finite set of elements in (0,1) needs to be present in (0,1).

If we select a value x \in (0,1) we want this:

max(U_1, ....,U_n) \leq x

And we can express this like that:

u_i \leq x for each possible i

We assume that the random variable u_i are independent and P)U_i \leq x) =x from the definition of an uniform random variable between 0 and 1. So we can find the cumulative distribution like this:

P(X \leq x) = P(U_1 \leq 1, ...., U_n \leq x) \prod P(U_i \leq x) =\prod x = x^n

And then cumulative distribution would be expressed like this:

0, x \leq 0

x^n, x \in (0,1)

1, x \geq 1

For each value x\in (0,1) we can find the dendity function like this:

f_X (x) = \frac{d}{dx} F_X (x) = nx^{n-1}

So then we have the pdf defined, and given by:

f_X (x) = n x^{n-1} , x \in (0,1)  and 0 for other case

And now we can find the expected value for the random variable X like this:

E(X) =\int_{0}^1 s f_X (x) dx = \int_{0}^1 x n x^{n-1}

E(X)= n \int_{0}^1 x^n dx = n [\frac{1}{n+1}- \frac{0}{n+1}]=\frac{n}{n+1}

6 0
3 years ago
1. In 2000, Florida's population was 16 million. Since 2000, the state's population has grown about 2% each
Yanka [14]

Answer:

13620000

Step-by-step explanation:

4 0
3 years ago
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