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Taya2010 [7]
3 years ago
12

Find the measure of a 3. { > 43 90° {{ 43 = [?] Fnter

Mathematics
1 answer:
OverLord2011 [107]3 years ago
4 0

Answer:

your question is not complete...

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Suppose that you have 7 cookies to distribute between 13 children.
Oduvanchick [21]

Answer

The answer and procedures of the exercise are attached in the following archives.

Step-by-step explanation:

You will find the procedures, formulas or necessary explanations in the archive attached below. If you have any question ask and I will aclare your doubts kindly.  

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Pat thinks of a number that is greater than 4 and less than 5.He doubles the number
soldi70 [24.7K]

Answer:

If you know your doubles, then it should be easy to go from 4 + 4 = 8 to 4 + 5 = 9.

Step-by-step explanation:

4 0
3 years ago
So i need help with the question below.
Shkiper50 [21]

Answer:

Option (1)

Step-by-step explanation:

Option (1)

3\frac{3}{9}+7\frac{6}{11}=10\frac{87}{99}

3\frac{3}{9}+7\frac{6}{11} =3+\frac{3}{9}+7+\frac{6}{11}

             =(3+7)+(\frac{3}{9}+\frac{6}{11})

             =10+(\frac{3}{9}\times \frac{11}{11})+(\frac{6}{11}\times \frac{9}{9})

             =10+(\frac{33}{99}+\frac{54}{99})

             =10+\frac{87}{99}

             =10\frac{87}{99}

True.

Option (2)

2\frac{3}{8}+6\frac{4}{5}=8\frac{12}{40}

2\frac{3}{8}+6\frac{4}{5}=2+\frac{3}{8}+6+\frac{4}{5}

             =(2+6)+(\frac{3}{8}+\frac{4}{5})

             =(8)+(\frac{3}{8}\times \frac{5}{5} +\frac{4}{5}\times \frac{8}{8})

             =8+(\frac{15}{40}+\frac{32}{40})

             =8+\frac{47}{40}

             =8+\frac{40}{40}+\frac{7}{40}

             =8+1+\frac{7}{40}

             =9+\frac{7}{40}

             =9\frac{7}{40}

False.

Option(3)

3\frac{3}{7}+4\frac{2}{3}=7\frac{2}{21}

3\frac{3}{7}+4\frac{2}{3}=(3+\frac{3}{7})+(4+\frac{2}{3})

             =(3+4)+(\frac{3}{7}+\frac{2}{3})

             =7+(\frac{3}{7}\times \frac{3}{3} +\frac{2}{3}\times \frac{7}{7})

             =7+(\frac{9}{21}+\frac{14}{21})

             =7+(\frac{23}{21})

             =7+(\frac{21}{21}+\frac{2}{21})

             =8+\frac{1}{21}

             =8\frac{1}{21}

False.

Option (4)

4\frac{5}{6}+5\frac{5}{7}=9\frac{10}{13}

4\frac{5}{6}+5\frac{5}{7}=4+\frac{5}{6}+5+\frac{5}{7}

             =(4+5)+(\frac{5}{6}+\frac{5}{7})

             =9+(\frac{5}{6}\times \frac{7}{7}+\frac{5}{7}\times \frac{6}{6})

             =9+(\frac{35}{42}+\frac{30}{42})

             =9+\frac{65}{42}

             =9+(\frac{42}{42}+\frac{23}{42})

             =9+1+\frac{23}{42}

             =10\frac{23}{42}

False.

Therefore, Option (1) is the answer.

8 0
3 years ago
The weight of crackers in a box is stated to be 16 ounces. The amount that the packaging machine puts in the boxes is believed t
krek1111 [17]

Answer:

99.99% probability that the mean weight of a 50-box case of crackers is above 16 ounces

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution

Problems of normally distributed samples are solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the zscore of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

In this problem, we have that:

\mu = 16.15, \sigma = 0.3, n = 50, s = \frac{0.3}{\sqrt{50}} = 0.0424

What is the probability that the mean weight of a 50-box case of crackers is above 16 ounces?

This is 1 subtracted by the pvalue of Z when X = 16. So

Z = \frac{X - \mu}{\sigma}

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{16 - 16.15}{0.0424}

Z = -3.54

Z = -3.54 has a pvalue of 0.0001

1 - 0.0001 = 0.9999

99.99% probability that the mean weight of a 50-box case of crackers is above 16 ounces

3 0
3 years ago
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