Someone plzz help me wit #3????

Graph the line with the equation y = - 1/3X + 2

BlackZzzverrR [31]

Answer:

the graph ^

Step-by-step explanation:

this is fun for no reason

7 0

3 years ago

Which logarithmic graph can be used to approximate the value of y in the equation 2y = 5? (5 points) The graph of function f of

Travka [436]

Answer:

Step-by-step explanation:

Taking the base 2 log of both sides, we get:

log-base 2 of 2 + log-base 2 of y = log-base 2 of 5, or

2 + log-base 2 of y = approx. 2.3, or

log-base 2 of y = approx 2.3 - 2, or

log-base 2 of y = approx 0.3

Please, if you are given a graph or graphs, share them along with all instructions for the problem at hand. Thank you.

8 0

4 years ago

Solid A has a volume of 28 in³. The scale factor of A to B is 1:2. What is the volume of Solid B?

PilotLPTM [1.2K]

Answer: 56in³

Step-by-step explanation:

Let the volume of solid B de denoted as x. Based on the information given in the question, we can solve further by:

1/2 = 28/x

Cross multiply

1 × x = 2 × 28

x = 56

Therefore, the volume of solid is 56in³.

4 0

3 years ago

Each day a manufacturing plant receives a large shipment of drums of Chemical ZX-900. These drums are supposed to have a mean fi

nikdorinn [45]

Answer:

0.9544 = 95.44% probability that the average fill for the 100 drums is between 49.88 and 50.12 gallons.

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