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gavmur [86]
3 years ago
14

1534 divided by 26 what is the answer help me out.

Mathematics
2 answers:
kirill [66]3 years ago
5 0

Answer: 59

Step-by-step explanation:

bonufazy [111]3 years ago
3 0

Answer:

59

Step-by-step explanation:

1534/26=59

It's 59 because I used a calculator

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5/4 divided by 2 (gives you the distance from the edge if you put the sticker in the center)

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I think this is correct. Hope it helps
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5 0
4 years ago
Consider the probabilities of people taking pregnancy tests. Assume that the true probability of pregnancy for all people who ta
Valentin [98]

Using conditional probability, it is found that there is a 0.8462 = 84.62% probability that a woman who gets a positive test result is truly pregnant.

<h3>What is Conditional Probability?</h3>

Conditional probability is the probability of one event happening, considering a previous event. The formula is:

P(B|A) = \frac{P(A \cap B)}{P(A)}

In which

  • P(B|A) is the probability of event B happening, given that A happened.
  • P(A \cap B) is the probability of both A and B happening.
  • P(A) is the probability of A happening.

In this problem, the events are:

  • Event A: Positive test result.
  • Event B: Pregnant.

The probability of a positive test result is composed by:

  • 99% of 10%(truly pregnant).
  • 2% of 90%(not pregnant).

Hence:

P(A) = 0.99(0.1) + 0.02(0.9) = 0.117

The probability of both a positive test result and pregnancy is:

P(A \cap B) = 0.99(0.1)

Hence, the conditional probability is:

P(B|A) = \frac{0.99(0.1)}{0.117} = 0.8462

0.8462 = 84.62% probability that a woman who gets a positive test result is truly pregnant.

You can learn more about conditional probability at brainly.com/question/14398287

7 0
2 years ago
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