Simplest form of 3/4+1/12

There are 12 people having lunch. Each person wants 1/3 of a sub sandwich. How many whole sub sandwich are needed

Oliga [24]

12/3= 4
Need 4 whole sub sandwiches in orders for everyone to get 1/3 of a sandwich

3 0

3 years ago

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Solve x-5y=-30, 3x+5y=10 show your work

marin [14]

1) x = 5y - 30

2) x = - 1.6y + 3.3

<em>im assuming these are 2 different questions</em>

<h3>Explanation:</h3><h3>1)</h3>

Start with the equation:

x - 5y= -30

add 5y to both sides:

x = 5y - 30

Your answer is x = 5y - 30

Start with the equation:

3x+5y=10

subtract 5y from both sides:

3x = -5y + 10

divide by 3 to get x singular

x = - 1.6y + 3.3

Your answer is x = - 1.6y + 3.3

Hope this helps :)

6 0

2 years ago

Evaluate the expression for the given value of the variable(s).

Lesechka [4]

The answer to what you have there is -55 using order of operations. 5 times -6 is -30. 5 times -5 is -25. add. You get -55.

3 0

2 years ago

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HELP PLEASE ASAP!!!!

topjm [15]

You have to find the angle for it try it!!!!!!!!!!

7 0

2 years ago

The scores on the GMAT entrance exam at an MBA program in the Central Valley of California are normally distributed with a mean

Kaylis [27]

Answer:

58.32% probability that a randomly selected application will report a GMAT score of less than 600

93.51% probability that a sample of 50 randomly selected applications will report an average GMAT score of less than 600

98.38% probability that a sample of 100 randomly selected applications will report an average GMAT score of less than 600

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:

$\mu = 591, \sigma = 42$

What is the probability that a randomly selected application will report a GMAT score of less than 600?

This is the pvalue of Z when X = 600. So

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

$Z = \frac{600 - 591}{42}$

$Z = 0.21$

$Z = 0.21$ has a pvalue of 0.5832

58.32% probability that a randomly selected application will report a GMAT score of less than 600

What is the probability that a sample of 50 randomly selected applications will report an average GMAT score of less than 600?

Now we have $n = 50, s = \frac{42}{\sqrt{50}} = 5.94$

This is the pvalue of Z when X = 600. So

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

$Z = \frac{600 - 591}{5.94}$

$Z = 1.515$

$Z = 1.515$ has a pvalue of 0.9351

93.51% probability that a sample of 50 randomly selected applications will report an average GMAT score of less than 600

What is the probability that a sample of 100 randomly selected applications will report an average GMAT score of less than 600?

Now we have $n = 50, s = \frac{42}{\sqrt{100}} = 4.2$

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

$Z = \frac{600 - 591}{4.2}$

$Z = 2.14$

$Z = 2.14$ has a pvalue of 0.9838

98.38% probability that a sample of 100 randomly selected applications will report an average GMAT score of less than 600

8 0

3 years ago