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Elena-2011 [213]
3 years ago
8

If you can get an answer to any question, what would you ask? You toss a fair coin 4 times. What is the probability that (round

to 4 decimal places) a) you get all Heads? b) you get at least one Tail?
Mathematics
1 answer:
Andrew [12]3 years ago
4 0

Answers:

a) 0.0625

b) 0.9375

==================================================

Work Shown:

The probability of landing on heads is 1/2 = 0.5 since both sides are equally likely to land on. Getting 4 heads in a row is (1/2)^4 = (0.5)^4 = 0.0625

The event of getting at least one tail is the complement of getting all four heads. This is because you either get all four heads or you get at least one tail. One or the other must happen. We subtract the result we got from 1 to get 1-0.0625 = 0.9375

You can think of it like this

P(getting all four heads) + P(getting at least one tail) = 1

The phrasing "at least one tail" means "one tail or more".

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Answer:

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Step-by-step explanation:

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we want to find the y intercept

-3 takes the spot of b therefore the y intercept is -3

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Many games depend on how a ball bounces. For example, if different basketballs rebounded differently, one basketball would bounc
Crank

Answer:

Basketball = 0.743

Step-by-step explanation:

Given

Tennis:

Starting Height = 200 cm

Rebound Height = 111 cm

Soccer Balls;

Starting Height = 200 cm

Rebound Height = 120 cm

Basketball:

Starting Height = 72 inches

Rebound Height = 53.5 inches

Squash:

Starting Height = 100 inches

Rebound Height = 29.5 inches

For measuring the bounciness of a ball, one needs that starting Height of and the rebound Height of that ball which have been listed out above.

Calculating the rebound ratio of each balls.

Rebound Ratio = Rebound Height/Starting Height

Tennis: 111/200= 0.556

Soccer Balls: 120/200 = 1.667

Basketball: 53.5/72 = 0.743

Squash: 29.5/100 = 0.295

From the rebounding ratio calculated above, it can be seen that basketball has the highest rebound ratio of 0.743 and is the bounciest of all whole Squash has the least rebound of 0.295 ratio, hence it is the least bounce of all.

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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

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

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