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3 years ago

Help me please!!!!!!!!!!!!!!!!!

Mathematics

1 answer:

iren [92.7K]3 years ago

5 0

Answer:

A. x^6

Step-by-step explanation:

$z = {y}^{2} = {( {x}^{3} )}^{2} = {x}^{3 \times 2} = {x}^{6}$

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There was 420 hamburger and cheeseburgers. The cheeseburgers sold two times then the hamburger. How many hamburgers were sold

madam [21]

The answer is 140.

If there are 140 hamburgers sold, and there were 2x as many cheeseburgers sold, that adds up to 420.

140 x 2 = 280 (Cheeseburgers)
So there were 280 cheeseburgers sold.

280 (Cheeseburgers) + 140 (Hamburgers) = 420 altogether.

Hope this helps!

5 0

3 years ago

A recent survey found that 86% of employees plan to devote at least some work time to follow games during the NCAA Men's Basketb

trasher [3.6K]

Answer:

4.18% probability that less than 80% of this sample will devote work time to follow games

Step-by-step explanation:

Normal probability distribution

When the distribution is normal, we use 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 $s = \frac{\sigma}{\sqrt{n}}$ .

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean $\mu = p$ and standard deviation $s = \sqrt{\frac{p(1-p)}{n}}$

In this question, we have that:

$p = 0.86, n = 100$

$\mu = 0.86, s = \sqrt{\frac{0.86*0.14}{100}} = 0.0347$

What is the probability that less than 80% of this sample will devote work time to follow games?

This is the pvalue of Z when X = 0.8. So

$Z = \frac{X - \mu}{\sigma}$

By the Central Limit Theorem

$Z = \frac{X - \mu}{s}$

$Z = \frac{0.8 - 0.86}{0.0347}$

$Z = -1.73$

$Z = -1.73$ has a pvalue of 0.0418

4.18% probability that less than 80% of this sample will devote work time to follow games

7 0

3 years ago

? cm<br> 3 cm<br> 7 cm<br> 4 cm<br> 7 cm<br> Missing length

Ket [755]

Answer:

5 cm

7cm

Step-by-step explanation:

8 0

3 years ago

Witch is grater 3/4 or 11/16 ??

kow [346]

<h3>Hey there! </h3><h3> $\frac{3}{4}$ → $0.75$ → $0.75$ %</h3><h3> $\frac{11}{16}$ → $0.6875$ → $0.68$ % </h3><h3>So, the one that is $GREATER$ is: $\frac{3}{4}$ because $75$ % is bigger than</h3><h3> $68$ %</h3><h3>Good luck on your assignment and enjoy your day! </h3><h3>~ $LoveYourselfFirst:)$ </h3>

5 0

3 years ago

The standard deviation of the tap water data is 1.086. The standard deviation of the salt water data is 1.107. Which explains wh

bulgar [2K]

A) The two distributions are each nearly symmetric

Correct on e2020

6 0

3 years ago

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