I need help quick!! 30 points!!!

Simplify -54 / 9 * -7 / 6

Artist 52 [7]

Answer:

7

Step-by-step explanation:

-54 / 9 * -7 / 6

Multiply and divide from left to right

-6 * -7/6

42 / 6

7

3 0

3 years ago

Read 2 more answers

HURRY NEED THIS ASAP. A company that manufactures golf balls produces a new type of ball that is supposed to travel significantl

Lera25 [3.4K]

The conclusion based on the mean of the ball and the distance traveled is D. Inferences cannot be made about all the golf balls produced on that day.

<h3>How to deduce the inference?</h3>

From the information given, a golf pro randomly selects a ball, not knowing the type of ball, hits it and end of the session, the mean distance traveled for the new type of golf ball was found to be greater than the mean distance for the original-style golf ball.

In this case, inferences cannot be made about all the golf balls produced on that day; however, the conclusion can be made that the new type of golf balls travel farther than the original type of golf ball for this golf pro.

Learn more about mean on:

brainly.com/question/1136789

5 0

2 years ago

Scores on an aptitude test are distributed with a mean of 220 and a standard deviation of 30. The shape of the distribution is u

Evgen [1.6K]

Answer:

P(215<X<225) = 0.7620

Step-by-step explanation:

The shape of the distribution is unknow, however, the shape of the sampling distributions of the sample mean is approximately normal due to 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 $s = \frac{\sigma}{\sqrt{n}}$ .