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2 years ago

I srsly need help this answer is not right and idk which one is

Mathematics

1 answer:

Zanzabum2 years ago

8 0

I'm not to well with this but try using photo math also they will show you exactly how to solve it

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Constance's car has a 12-gallon gas

antiseptic1488 [7]

Answer:

7.5 hours

Step-by-step explanation:

Constance's car has a 12-gallon gas tank.

She can travel 25 miles on one gallon of gas, so she can travel

$25\cdot 12=300$ miles using all gas from the tank.

Constance begins with a full tank of gas and drives at a constant rate of 40 miles per hour.

So, Constance can drive for

$300 : 40=7.5$ hours.

3 0

2 years ago

2. Write an equation in slope intercept form with the given Information Goes through points (1, 8) and (5, 0)

pantera1 [17]

Answer:

$y = -2x + 10$

Step-by-step explanation:

Slope: $m = \frac{y_{2}-y_{1} }{x_{2}-x_{1}}$

Slope-Intercept Form: $y=mx+b$

$m=\frac{8-0}{1-5}$

$m = -2$

$y = -2x + b$

$0 = -2 (5)+b$

$0=(-10)+b$

$b = 10$

$y = -2x + 10$

8 0

2 years ago

In the university library elevator there is a sign indicating a 16-person limit as well as a weight limit of 2750 pounds. Suppos

Alona [7]

Answer:

0.039 = 3.9% probability that the random sample of 16 people in the elevator will exceed the weight limit

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