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forsale [732]
3 years ago
12

Five times the sum of a number (x) and three is equal to the sum of that number (x) and fifteen.

Mathematics
2 answers:
tamaranim1 [39]3 years ago
6 0
5(x+3)=x+15
its simple
Mariana [72]3 years ago
4 0
5(x + 3) = x + 15....distribute
5x + 15 = x + 15...subtract x from both sides, subtract 15 from both sides
5x - x = 15 - 15
4x = 0
x = 0 <=
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27; The first stack is 3 x 3 (= 9). You then multiply 9 by 3 (for each of the 3 stacks). Basically, 3 x 3 x 3.
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Which expression is equivalent to (73)-2
padilas [110]

Answer:

73*-2 =-146 you have to multiply the 73 to the -2

Step-by-step explanation:

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3 years ago
Question 6 (2 points)
irinina [24]

to inverse a equation make all y's x and andy x's y

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3 0
3 years ago
A representative from the National Football League's Marketing Division randomly selects people on a random street in Kansas Cit
Orlov [11]

Using the binomial distribution, we have that:

a) 0.1024 = 10.24% probability that the marketing representative must select 4 people to find one who attended the last home football game.

b) 0.2621 = 26.21% probability that the marketing representative must select more than 6 people to find one who attended the last home football game.

c) The expected number of people is 4, with a variance of 20.

For each person, there are only two possible outcomes. Either they attended a game, or they did not. The probability of a person attending a game is independent of any other person, which means that the binomial distribution is used.

Binomial probability distribution  

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}  

C_{n,x} = \frac{n!}{x!(n-x)!}

The parameters are:

  • p is the probability of a success on a single trial.
  • n is the number of trials.
  • p is the probability of a success on a single trial.

The expected number of <u>trials before q successes</u> is given by:

E = \frac{q(1-p)}{p}

The variance is:

V = \frac{q(1-p)}{p^2}

In this problem, 0.2 probability of a finding a person who attended the last football game, thus p = 0.2.

Item a:

  • None of the first three attended, which is P(X = 0) when n = 3.
  • Fourth attended, with 0.2 probability.

Thus:

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

P(X = 0) = C_{3,0}.(0.2)^{0}.(0.8)^{3} = 0.512

0.2(0.512) = 0.1024

0.1024 = 10.24% probability that the marketing representative must select 4 people to find one who attended the last home football game.

Item b:

This is the probability that none of the first six went, which is P(X = 0) when n = 6.

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

P(X = 0) = C_{6,0}.(0.2)^{0}.(0.8)^{6} = 0.2621

0.2621 = 26.21% probability that the marketing representative must select more than 6 people to find one who attended the last home football game.

Item c:

  • One person, thus q = 1.

The expected value is:

E = \frac{q(1-p)}{p} = \frac{0.8}{0.2} = 4

The variance is:

V = \frac{0.8}{0.04} = 20

The expected number of people is 4, with a variance of 20.

A similar problem is given at brainly.com/question/24756209

3 0
2 years ago
Question 1 (Multiple Choice Worth 1 points)
Oksi-84 [34.3K]

Sorry I don't know but i bet more can exolain.

4 0
3 years ago
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