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Lilit [14]
3 years ago
7

(1/6) ÷ 2 =

Mathematics
1 answer:
laila [671]3 years ago
6 0

Hi There!

(1/6) ÷ 2 = 1/12

1 ÷ 1/6 = 6

(1/10) ÷ 4 = 1/40

(1/5) ÷ 3 = 1/15

3 ÷ (1/2) = 6

2 ÷ (6/13) = 26/6 = 4 2/6 = 4 1/3

1 ÷ (3/19) = 19/3 = 6 1/3

(1/2) ÷ (1/2) = 1

(1/2) ÷ (7/9) = 9/14

(8/9) ÷ (2/3) = 24/18 = 1 6/18 = 1 1/3

Hope This Helps :)

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Reasoning:
6 0
3 years ago
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To reduce laboratory​ costs, water samples from two public swimming pools are combined for one test for the presence of bacteria
givi [52]

Answer:

The probability of a positive test result is 0.017919

Option C is correct.

The probability is quite​ low, indicating that further testing of the individual samples will be a rarely necessary event.

Step-by-step explanation:

Probability of finding bacteria in one public swimming pool = 0.009

We now require the probability of finding bacteria in the combined test of two swimming pools. This probability is a sum of probabilities.

Let the two public swimming pools be A and B respectively.

- It is possible for public swimming pool A to have bacteria and public swimming pool B not to have bacteria. We would obtain a positive result from testing a mixed sample of both public swimming pools.

- It is also possible for public swimming pool A to not have bacteria and public swimming pool B to have bacteria. We would also obtain a positive result from testing a mixed sample of both public swimming pools.

- And lastly, it is possible that both swimming pools both have bacteria in them. We will definitely get a positive result from this too.

So, if P(A) is the probability of the event of bacteria existing in public swimming pool A

And P(B) is the probability of the event of bacteria existing in public swimming pool B

P(A') and P(B') represent the probabilities of bacteria being absent in public swimming pool A and public swimming pool B respectively.

P(A) = P(B) = 0.009

P(A') = P(B') = 1 - 0.009 = 0.991

Since the probabilities for each public swimming pool is independent of the other.

P(A or B) = P(A n B') + P(A' n B) + P(A n B)

= P(A)×P(B') + P(A')×P(B) + P(A)×P(B)

= (0.009×0.991) + (0.991×0.009) + (0.009×0.009)

= 0.008919 + 0.008919 + 0.000081

= 0.017919

Evidently, a probability of 0.017919 (1.7919%) indicates an event with a very low likelihood. A positive result is expected only 1.7919% of the time.

Hence, we can conclude that the probability is quite​ low, indicating that further testing of the individual samples will be a rarely necessary event.

Hope this Helps!!!

4 0
3 years ago
Read 2 more answers
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sergiy2304 [10]

\bf \begin{cases} \boxed{y}=6x-11\\ \cline{1-1} -2x-3y=-7 \end{cases}\qquad \implies \stackrel{\textit{substituting \underline{y} in the 2nd equation}}{-2x-3\left( \boxed{6x-11} \right)=-7}

\bf -2x-18x+33=-7\implies -20x+33=-7\implies -20x=-40 \\\\\\ x=\cfrac{-40}{-20}\implies \blacktriangleright x=2 \blacktriangleleft \\\\[-0.35em] ~\dotfill\\\\ \stackrel{\textit{since we know that }}{y=6x-11}\implies y=6(2)-11\implies y=12-11\implies \blacktriangleright y=1 \blacktriangleleft \\\\[-0.35em] \rule{34em}{0.25pt}\\\\ ~\hfill (2,1)~\hfill

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3 years ago
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The estimated probability of a football player scoring a touchdown during a particular game is 39%. Of several simulations of th
VLD [36.1K]

Answer:

The percentage of the simulations of two games that the football player would most likely get a touchdown in each of the two games = 15.21%

Step-by-step explanation:

The probability of scoring a touchdown in one game for the football player = 39% = 0.39

Probability of scoring a touchdown in each of the two consecutive games = (Probability of scoring a touchdown in the first game) × (Probability of scoring a touchdown in the second game)

Since the probability of scoring a touchdown in each game the football player plays in is independent of one another.

Probability of scoring a touchdown in the first game = Probability of scoring a touchdown in the second game = 0.39

Probability of scoring a touchdown in each of the two consecutive games = 0.39 × 0.39 = 0.1521

If 100 simulations of the two games are made, the player scores in each of the two games in 15.21 of them, hence, the percentage of the simulations that the football player would most likely get a touchdown in each of the two games = 15.21%

Hope this Helps!!

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