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yan [13]
3 years ago
5

What is 1/5 +1/4 please help thank you

Mathematics
1 answer:
Semmy [17]3 years ago
5 0
To add fractions, you find the least common multiple.
But, a faster way would be multiply the two denominators together:

x/20 + /20 
How many times does 4 go into 20? 5 times. 5 times 1 equals 5.
5/20 + x/20
How many times does 5 go into 20 4 times? 4 times 1 equals 4.

5/20 + 4/20 = 9/20. This is the final answer because it can't be simplified any more.
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<img src="https://tex.z-dn.net/?f=%20%5Cfrac%7Bx%7D%7B5%7D%2B%5Cfrac%7B3x%7D%7B15%7D%3D%5Cfrac%7B2x%7D%7B3%7D%20%7D%20" id="TexF
Bezzdna [24]
Multiply all terms by 15
3x+3x= 10x+30

Combine like terms
6x=10x+30

Subtract 10x from both sides
-4x=30

Divide both sides by -4
x= -7.5

Final answer: -7.5
4 0
3 years ago
Ugh geez can ANYONE help with 2 questions????????????
just olya [345]
What's the 2 question
5 0
3 years ago
Evaluate 4+ (-2) – (-3) – 6.​
zhuklara [117]

Answer:

-1

Step-by-step explanation:

4 + (-2) - (-3) - 6

4 - 2 + 3 - 6

2 - 3

-1

3 0
3 years ago
Find the measure of 659<br> 670<br> In
sineoko [7]
The question doesn’t make sense.
3 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
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