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lbvjy [14]
2 years ago
13

The tables represent two linear functions in a system.

Mathematics
1 answer:
stich3 [128]2 years ago
3 0

Answer:

how?

Step-by-step explanation:

i didnt get this question

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I’m stuck I need help
arlik [135]

Answer:

X=6

Step-by-step explanation:

First step isolate the variable;2x=12

Simplify;x=12/2=6

8 0
2 years ago
36 x 69 in area model
inysia [295]
ANSWER: 2484

(Alternative forms): 2.484 × 10³
8 0
2 years ago
What is the height of a cylinder with a volume of 1,899.7 cubic inches and a radius of 11 inches?
FrozenT [24]


Not 100% sure. 

Height = 37.81inches


8 0
3 years ago
Read 2 more answers
Every evening, two weather stations issue weather forecast for the next day. The weather forecasts are independent. On average,
EleoNora [17]

Answer:

The probability is 0.6923

Step-by-step explanation:

Let's call R the event that the next day rains, S the event that the next day has sunny weather, R2 the event that the station 2 predicts rain and S1 the event that station 1 predict sunny weather.

The probability that the next day has sunny weather given that station 1 predicts sunny weather for the next day and station 2 predicts rain is calculated as:

P(S/S1∩R2) = P(S∩S1∩R2)/P(S1∩R2)

Where P(S1∩R2) = P(R∩S1∩R2) + P(S∩S1∩R2)

So, the probability P(R∩S1∩R2) that the next day rains, Station 1 predicts sunny weather and Station 2 predicts Rain is calculate as:

P(R∩S1∩R2) = 0.5 * 0.1 * 0.8 = 0.04

Because 0.5 is the probability that the next day rains, 0.1 is the probability that station 1 predicts sunny weather given that it is going to rain and 0.8 is the probability that station 2 predicts rain given that it is going to rain.

At the same way, the probability P(S∩S1∩R2) that the next day has sunny weather, Station 1 predicts sunny weather and Station 2 predicts Rain is calculate as:

P(S∩S1∩R2) = 0.5 * 0.9 * 0.2 = 0.09

Then, the probability P(S1∩R2) that station 1 predicts sunny weather for the next day, whereas station 2 predicts rain is:

P(S1∩R2) = 0.04 + 0.09 = 0.13

Finally, P(S/S1∩R2) is:

P(S/S1∩R2) = 0.09/0.13 = 0.6923

6 0
3 years ago
;) yeah Imma just cheat my way through school you guys help a lot
amid [387]

Answer:

Thanks you too

Step-by-step explanation:

6 0
3 years ago
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