Which monomials are factors of 9x^4

George traveled 300 miles in 8 hours. How far could he travel in 4 hours if he traveled at the same rate?

Amiraneli [1.4K]

Divide 300 by 8 to find the unit rate
300/8= 37.5

He travels 37.5 miles per hour

If he travels 37.5 miles per hour, to find the amount in 4 hours we would do 37.5 times 4

37.5×4=150

In 4 hours he travels 150 miles

8 0

3 years ago

Read 2 more answers

Can to answer all 4 please?

Tasya [4]

1) A - yes, b - no, c - yes
2) false, true, false
3) 85p - 34%
xp - 66%
x = 165 - she has to read 165 more pages.
4) Sylvia earns 84/12 = 7$/hr
maximum she can earn is 7*15 = 105 $
she will earn 105$ if she works for 15 hours

5 0

3 years ago

Plz help ->

Paraphin [41]

Answer: ok so for 5 and 125 it is 65 and 25

for 1 and 9 it is 5 and 3 and for 4 and 9 it is 13/2 and 6

6 0

3 years ago

The mean of a population is 74 and the standard deviation is 15. The shape of the population is unknown. Determine the probabili

Lena [83]

Answer:

a) 0.0548 = 5.48% probability of a random sample of size 36 yielding a sample mean of 78 or more.

b) 0.9858 = 98.58% probability of a random sample of size 150 yielding a sample mean of between 71 and 77.

c) 0.5793 = 57.93% probability of a random sample of size 219 yielding a sample mean of less than 74.2

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