What is the product?

Satelite Corporation projects a year-end net income of $64,722. The net income represents 40% of its projected annual sales. Wha

Goryan [66]

Answer:

The projected annual sales of Satelite Corporation are $ 161,805.

Step-by-step explanation:

Given that Satellite Corporation projects a year-end net income of $ 64,722, and that the net income represents 40% of its projected annual sales, to determine the amount of the projected annual sales of the company the following calculation must be performed:

40 = 64.722

100 = X

(100 x 64,722) / 40 = X

6,472,200 / 40 = X

161.805 = X

Therefore, the projected annual sales of Satelite Corporation are $ 161,805.

4 0

3 years ago

Order the steps to show how to solve the equation 2(4x−11)+9=192(4x−11)+9=19.

Blababa [14]

I hope this helps you

4 0

3 years ago

The fracture strength of tempered glass averages 14 (measured in thousands of pounds per square inch) and has standard deviation

Wewaii [24]

Answer:

0.1587 = 15.87% probability that the average fracture strength of 100 randomly selected pieces of this glass exceeds 14.2.

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 normal distributions can be solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the z-score 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 p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem establishes 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 $s = \frac{\sigma}{\sqrt{n}}$ .