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dalvyx [7]
4 years ago
13

How are a common denominator and a common multiple alike and different?

Mathematics
2 answers:
Lubov Fominskaja [6]4 years ago
7 0

The <em><u>correct answer</u></em> is:

Both common denominators and common multiples are found the same way, but a denominator is strictly on the bottom of a fraction while a multiple is not.

Explanation:

To find a common denominator of two fractions, you find a number that both denominators of the given fractions will divide into.

To find a common multiple of two numbers, you find a number that both given numbers will divide into.

This is the same process for both things. However, once you find the common denominator, you then write it in the denominator of a fraction. Once you find the common multiple, you're finished.

victus00 [196]4 years ago
3 0
East common multiple is the smallest multiple both numbers can go into. (Example: the LCM of 10 and 4 is 20, because both 10 and 4 go into 20 and 20 is the smallest number both 10 and 4 can go into. You could just multiply them both, but you'd get 40 and since its a bigger number it would be harder to work with.)

<span>Least common denominator is just the least common multiple as a denominator. (Example: if you wanted to find the LCD of 5/7 and 1/10, you'd have to find the LCM of the demoniators (7 and 10) and then just use that as the denominator when adding fractions with unlikely denominators.) Sorry for such a long answer :P</span>
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The perimeter of the triangle, namely the sum of all its 3 sides, is 110.

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7 0
4 years ago
The distribution of weights for newborn babies is approximately normally distributed with a mean of 7.4 pounds and a standard de
blsea [12.9K]

Answer:

1. 15.87%

2.  6 pounds and 8.8 pounds.

3. 2.28%

4. 50% of newborn babies weigh more than 7.4 pounds.

5. 84%

Step-by-step explanation:

We are given the following information in the question:

Mean, μ = 7.4 pounds

Standard Deviation, σ = 0.7 pounds

We are given that the distribution of weights for newborn babies is a bell shaped distribution that is a normal distribution.

Formula:

z_{score} = \displaystyle\frac{x-\mu}{\sigma}

1.Percent of newborn babies weigh more than 8.1 pounds

P(x > 8.1)

P( x > 8.1) = P( z > \displaystyle\frac{8.1 - 7.4}{0.7}) = P(z > 1)

= 1 - P(z \leq 1)

Calculation the value from standard normal z table, we have,  

P(x > 8.1) = 1 - 0.8413 = 0.1587 = 15.87\%

15.87% of newborn babies weigh more than 8.1 pounds.

2.The middle 95% of newborn babies weight

Empirical Formula:

  • Almost all the data lies within three standard deviation from the mean for a normally distributed data.
  • About 68% of data lies within one standard deviation from the mean.
  • About 95% of data lies within two standard deviations of the mean.
  • About 99.7% of data lies within three standard deviation of the mean.

Thus, from empirical formula 95% of newborn babies will lie between

\mu-2\sigma= 7.4-2(0.7) = 6\\\mu+2\sigma= 7.4+2(0.7)=8.8

95% of newborn babies will lie between 6 pounds and 8.8 pounds.

3. Percent of newborn babies weigh less than 6 pounds

P(x < 6)

P( x < 6) = P( z > \displaystyle\frac{6 - 7.4}{0.7}) = P(z < -2)

Calculation the value from standard normal z table, we have,  

P(x < 6) =0.0228 = 2.28\%

2.28% of newborn babies weigh less than 6 pounds.

4. 50% of newborn babies weigh more than pounds.

The normal distribution is symmetrical about mean. That is the mean value divide the data in exactly two parts.

Thus, approximately 50% of newborn babies weigh more than 7.4 pounds.

5. Percent of newborn babies weigh between 6.7 and 9.5 pounds

P(6.7 \leq x \leq 9.5)\\\\ = P(\displaystyle\frac{6.7 - 7.4}{0.7} \leq z \leq \displaystyle\frac{9.5-7.4}{0.7})\\\\ = P(-1 \leq z \leq 3)\\\\= P(z \leq 3) - P(z < -1)\\= 0.9987 -0.1587= 0.84 = 84\%

84% of newborn babies weigh between 6.7 and 9.5 pounds.

7 0
3 years ago
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