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3 years ago

Joséphine noticed that out of 10 e-mails she

Mathematics

2 answers:

Lynna [10]3 years ago

6 0

Answer:

The answer is C

I did the quiz on edge

tangare [24]3 years ago

6 0

Answer:

The answer is 70

Step-by-step explanation:

no cap

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Line HJ bisects BC at point H<br> BH = 5x - 1<br> and HC =4x + 3<br> Frd the length of BC

Levart [38]

Answer:

Step-by-step explanation:

5x - 1 = 4x + 3

x - 1 = 3

x = 4

5(4) - 1 + 4(4) + 3

20 - 1 + 16 + 3

19 + 16 + 3 = 35 + 3 = 38

8 0

3 years ago

At Munder Difflin Paper Company, the manager Mitchell Short randomly places golden sheets of paper inside of 30% of their paper

Korvikt [17]

Answer:

90.67% probability that John finds less than 7 golden sheets of paper

Step-by-step explanation:

For each container, there are only two possible outcomes. Either it contains a golden sheet of paper, or it does not. The probability of a container containing a golden sheet of paper is independent of other containers. So we use the binomial probability distribution to solve this question.

Binomial probability distribution

The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.

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

In which $C_{n,x}$ is the number of different combinations of x objects from a set of n elements, given by the following formula.

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

And p is the probability of X happening.

At Munder Difflin Paper Company, the manager Mitchell Short randomly places golden sheets of paper inside of 30% of their paper containers.

This means that $p = 0.3$

14 of these containers of paper.

This means that $n = 14$

What is the probability that John finds less than 7 golden sheets of paper?

$P(X < 7) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3) + P(X = 4) + P(X = 5) + P(X = 6)$

In which

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

$P(X = 0) = C_{14,0}.(0.3)^{0}.(0.7)^{14} = 0.0068$

$P(X = 1) = C_{14,1}.(0.3)^{1}.(0.7)^{13} = 0.0407$

$P(X = 2) = C_{14,2}.(0.3)^{2}.(0.7)^{12} = 0.1134$

$P(X = 3) = C_{14,3}.(0.3)^{3}.(0.7)^{11} = 0.1943$

$P(X = 4) = C_{14,4}.(0.3)^{4}.(0.7)^{10} = 0.2290$

$P(X = 5) = C_{14,5}.(0.3)^{5}.(0.7)^{9} = 0.1963$

$P(X = 6) = C_{14,6}.(0.3)^{6}.(0.7)^{8} = 0.1262$

$P(X < 7) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3) + P(X = 4) + P(X = 5) + P(X = 6) = 0.0068 + 0.0407 + 0.1134 + 0.1943 + 0.2290 + 0.1963 + 0.1262 = 0.9067$

90.67% probability that John finds less than 7 golden sheets of paper

7 0

2 years ago

Please answer this!!! No links !!!

stealth61 [152]

My work for your question

8 0

2 years ago

10x +1 12x-5 solve for x

dimulka [17.4K]

Answer:

x = 3

Step-by-step explanation:

10x + 1 = 12x - 5

Subtract 1 from each side

10x = 12x - 6

Subtract 12x from each side

-2x = -6

Divided by -2

x = 3

5 0

3 years ago

A game of chance has a spinner with five equal-sized sections, The results of 625 spins are shown below. For which color is the

andrew-mc [135]

The color that has the greatest difference between the theoretical and experimental probability is yellow.

<h3>Which color has the greatest difference?
</h3>

Theoretical probability of each color = number of color in each section / total number of sections

1/5 = 0.2

Experimental probability is based on the result of an experiment that has been carried out multiples times

Experimental probability

Experimental probability of choosing orange = 118 / 625 = 0.19

Difference = 0.2 - 0.19 = 0.01

Experimental probability of choosing purple = 137 / 625 = 0.22

Difference 0.22 - 0.2 = 0.02

Experimental probability of choosing brown = 122 / 625 = 0.20

0.2 - 0.2 = 0

Experimental probability of choosing yellow = 106 / 625 = 0.17

0.20 - 0.1696 = 0.0304

Experimental probability of choosing green = 142 / 625 = 0.23

0.2272 - 0.20 = 0.0272

To learn more about experimental probability, please check: brainly.com/question/23722574

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4 0

2 years ago