What is the Volume of this Prism?

2. It takes 39,090 gallons of water to manufacture a new car. Sammy thinks that rounds up to about 40,000

Ainat [17]

Answer:

Susie rounded to the nearest thousandth.

Step-by-step explanation:

since the 100th place is 0 it would round down to 39,000 when you are rounding to the nearest thousand.

8 0

3 years ago

At Best Burgers, Jack collected sales data on the type of side order served with each type of burger purchased for a week. Jack

horsena [70]

The <em><u>correct answers</u></em> are:

60 pounds of onion rings and 60 hamburgers.

Explanation:

Jack serves a half pound of onion rings with every burger. He serves 120 bacon cheeseburgers. To find the number of pounds of onion rings, we multiply 1/2 pound by 120 burgers:

1/2(120) = 1/2(120/1) = (1*120)/(2*1) = 120/2 = 60 pounds of onion rings.

There were 8 hamburgers served out of the first 40 orders. If this rate continues, then to find the number of hamburgers out of 300 orders, we multiply 8/40 by 300:

8/40(300) = 8/40(300/1) = (8*300)/(40*1) = 2400/40 = 60

There would be 60 hamburgers.

4 0

4 years ago

Read 2 more answers

Which is the best approximation for the value 140

zzz [600]

140 is a composite number. Factor pairs: 140 = 1 x 140, 2 x 70, 4 x 35, 5 x 28, 7 x 20, 10 x 14. Factors of 140: 1, 2, 4, 5, 7, 10, 14, 20, 28, 35, 70, 140. Prime factorization: 140 = 2 x 2 x 5 x 7, which can also be written 140 = 2² x 5 x 7

4 0

3 years ago

What is the z-score of a newborn who weighs 4,000 g?.

vagabundo [1.1K]

The z-score of the considered newborn having 4,000 g weight is $\dfrac{4000 - \mu}{\sigma}$

<h3>How to get the z scores?</h3>

If we've got a normal distribution, then we can convert it to standard normal distribution and its values will give us the z score.

If we have

$X \sim N(\mu, \sigma)$

(X is following normal distribution with mean $\mu$ and standard deviation $\sigma$ )

then it can be converted to standard normal distribution as

$Z = \dfrac{X - \mu}{\sigma}, \\\\Z \sim N(0,1)$

(Know the fact that in continuous distribution, probability of a single point is 0, so we can write

$P(Z \leq z) = P(Z < z) )$

Also, know that if we look for Z = z in z tables, the p value we get is

$P(Z \leq z) = \rm p \: value$

For the considered case, the statement in the problem is missing the mean weight of the newborn and standard deviation of the data set of weights of newborn.

Thus, for them, we can consider variables in place of their actual values.

Let we have: