Dinner cost 45.50 you left a 20% tip how much money did you spend altogether

Digit realizes that some members of the audience cannot see the bride and groom due to the current seating arrangement. Therefor

DiKsa [7]

Answer:

A dilation

Step-by-step explanation:

i

3 0

2 years ago

Determine if the following relation represents a function or not.

artcher [175]

Answer:

It is a function.

Step-by-step explanation:

Functions are relations in which one domain value is assigned to exactly one range value. The x-value must not repeat in the relation set for it to be a function.

{(2,3), (4,3), (6,3), (5,9), (3,9)}

There are no repeating x-values given.

The relation should be a function.

Hope this helps.

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