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3 years ago

I need help ASAP if you can help you are amazing.

Mathematics

1 answer:

olchik [2.2K]3 years ago

3 0

Answer (Note: the bold are answers):

First question answer:

Point = (3,1)

Slope = 3

y = 3x + b

(1) = 3(3) + b

1 = 9 + b

1 - 9 = b

-8 = b

y = 3x - 8

The second question answer:

y = mx + b

Get two points:

(3,-7) and (4,-11)

m = -11 - (-7) / 4 - 3

m = -11 + 7 / 1

m = -4 / 1

m = -4

b = + 3

y = -4x + 3

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Can you guys help me again lol-

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$93 per hour ?

125-405 = 280

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3 years ago

Read 2 more answers

The perimeter of the triangle is 30 cm.<br>The perimeter of the rectangle is also 30 cm.

mel-nik [20]

Answer:

The perimeter of the triangle is 30 cm.

The perimeter of the rectangle is also 30 cm.

Step-by-step explanation:

The perimeter of the triangle is 30 cm.

The perimeter of the rectangle is also 30 cm.

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3 years ago

George and Davon begin their hike at 9 a.m. one morning. They plan to hike from the 2 1/5 -mile marker to the 9 1/15 -mile marke

vredina [299]

Yes because when your multiply every thing together you’ll have 9/15 miles

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2 years ago

7 times a number is equal to 12 more than three times the number. Find the number.

Sonja [21]

7x=3x+12
-3x -3x
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6 0

3 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