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frez [133]
3 years ago
11

The large rectangle was reduced to create the small rectangle.What is the missing measure on the small rectangle?

Mathematics
1 answer:
klasskru [66]3 years ago
3 0

Answer:

x = 4 in

Step-by-step explanation:

scale factor of reduction is

\frac{6}{18} = \frac{1}{3}, thus

x = \frac{1}{3} × 12 = 4

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Solve for x. Solve for x solve for x solve for x
SIZIF [17.4K]

Answer:

x=29

Does the answer help you?

8 0
3 years ago
Find the length of side x in simplest radical form with a rational denominator <br> Help please!
myrzilka [38]

Answer:

x = 6

Step-by-step explanation:

x = 3 sin(90) / sin (30)

x = 3(1)/(1/2)

x = 3 ÷ \frac{1}{2}

x = 6

8 0
3 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
Helppppp pleaseeeee willlll appreciateddddd
kotegsom [21]
Most likely number 3 
we can guess the average of the two since we don't have the time to actually add all of them and divide and number 3 describes it the most  
3 0
3 years ago
Can people help me on this please I need it!!! It’s really important
Firdavs [7]

Answer:

62

Step-by-step explanation:

The total of a triangle is 180

so 78+48 is 118

180-118=62

5 0
3 years ago
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