Find he measure of xi<br> 5x-2<br> H

What are the intercepts of the graphed function?

Georgia [21]

Answer:

The first option.

Step-by-step explanation:

5 0

3 years ago

What is the meaning of the point (25, 20)?

Reil [10]

Answer:

(25, 20 ) represents that the dimension of the coral is 25 feet long and 20 feet wide.

Step-by-step explanation:

The general representation P(x,y) represents the Cartesian Representation of a point in a 2 Dimension.

Here, x represents the distance of the point P from y axis to the x axis.

and y represents the distance of the point P from x axis to the y axis.

(x, y) together gives the 2 dimensional representation of the point P.

Now here, the given coordinates are (25, 20)

So, here x = 25 and y = 20

So, (25, 20 ) represents that the dimension of the coral is 25 feet long and 20 feet wide.

Hence, option 3 is the most appropriate.

6 0

3 years ago

A manufacturer knows that their items have a normally distributed length, with a mean of 15.4 inches, and standard deviation of

Masteriza [31]

Answer:

0.9452 = 94.52% probability that their mean length is less than 16.8 inches.

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