Which representation does not show y as a function of x

The sales tax rate is 4.3064.306% for the city and 44% for the state. Find the total amount paid for 33 boxes of chocolates at

svp [43]

Answer:

The Total amount of of 33 boxes of chocolates including taxes is $838.358

Step-by-step explanation:

Given as :

The sales tax rate for city = 4.306%

The sales tax rate for the state = 44%

Total number of boxes = 33

The price of each chocolates = $17.13

So , The price of 33 boxes of chocolates = $17.13 × 33

I.e The price of 33 boxes of chocolates = $565.29

Now total tax including state and city = 4.306% + 44% = 48.306 %

So, The tax amount paid for 33 boxes of chocolates = 48.306 % of $565.29

∴ The tax amount paid for 33 boxes of chocolates = 48.306 % × $565.29

= 0.48306× $565.29

= $273.068

∴ The Total amount of of 33 boxes of chocolates including taxes = $565.29 + $273.068 = $838.358

Hence The Total amount of of 33 boxes of chocolates including taxes is $838.358 . Answer

4 0

3 years ago

Pls answer with explanation!

patriot [66]

Answer:

3,750 cars.

Step-by-step explanation:

We are given that the equation:

$y=9000-2.4x$

Models the relationsip between y, the number of unfilled seats in the stadium, and x, the number of cars in the parking lot.

We want to determine the number of cars in the parking lot when there are no unfilled seats in the stadium.

When there are no unfilled seats in the stadium, y = 0. Thus:

$0=9000-2.4x$

Solve for x. Subtract 9000 from both sides:

$-2.4x=-9000$

Divide both sides by -2.4:

$x=3750$

So, there will be 3,750 cars in the parking lot when there are no unfilled seats in the stadium.

4 0

3 years ago

Annual starting salaries in a certain region of the U. S. for college graduates with an engineering major are normally distribut

defon

Answer:

0.8665 = 86.65% probability that the sample mean would be at least $39000

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