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Korvikt [17]
3 years ago
12

Sarah married 8 times ,the first marriage her husband cheated leaving her with 2 children,her second husband died leaving her wi

th three children ,all her other marriages ended in disaster leaving her with one more than the last .How many children does Sarah have all together.
Mathematics
1 answer:
LekaFEV [45]3 years ago
3 0

Answer:

probably 6 or 11 not too sure but that's my answer

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Please give me the answer.
VikaD [51]

Answer:

(2,-7)

Step-by-step explanation:

Plug in the numbers to test and see if it gives you -17 and -8.

Option 1. 2(-4)+3(2)

= -8+6 = -2. Not it.

Option 2. 2(2)+3(-7)

4 - 21 = -17 Works. Try the second equation to make sure.

3(2)+2(-7)

6-14 = -8. Works.

(2,-7) is the answer.

4 0
3 years ago
3(x+6)+2x-5=-2(x+1)+10
Leto [7]

Step-by-step explanation:

3x+18+2x-5= -2x+-2+10

combining like terms

3x+2x+2x=5-2+10-18

7x=-5

x=-5/7

8 0
3 years ago
Read 2 more answers
A sandwich shop has 40 stores and 80% of the stores are in California. The rest of the stores are in Nevada how many stores are
Elina [12.6K]

Answer:

32 are in California and 8 are in Nevada.

Step-by-step explanation:

You multiply 40 by 0.80. You then get 32. That's your answer.

5 0
3 years ago
Help plzzz will give brainliest
Rasek [7]

Answer:

the amswer is 5 hope this helps you

3 0
3 years ago
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
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