What is the answer to 2(8 + 7)

Two cars leave town at the same time going in the same direction on the same road.One travels 32 mi/h and the other travels 47 m

gladu [14]

In 4.6 hours they will be 69 miles apart

3 0

2 years ago

QUESTION: The area of a base of a cylinder is represented by , where d is the diameter. A function representing the area of the

MakcuM [25]

Answer:

c

Step-by-step explanation:

5 0

3 years ago

Read 2 more answers

SOLVE FOR J. <br><br> j+11.98≥-7.02 <br> (that is not a subtraction sign its a negative sign!!)

LiRa [457]

J>-19

Hope that helps

7 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 $s = \frac{\sigma}{\sqrt{n}}$ .