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3 years ago

Which answers describe the shape below? CHECK ALL THAT APPLY!

Mathematics

1 answer:

Ipatiy [6.2K]3 years ago

4 0

Answer:

Parallelogram, Quadrilateral,Rhombus

Step-by-step explanation:

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Ariel was told the x intercept and the y intercept of a line with a positive slope. Yet, it was impossible for Ariel to find the

alexdok [17]

A line has the following standard equation form:

y = m x + b

where m is the slope and b is the y intercept

So if Ariel cannot find the slope, then this would only mean that m = 0, there is no slope. And hence the line is either a straight vertical line or straight horizontal line.

Answer:

<span>There is no slope</span>

8 0

3 years ago

The radius of a sphere is 6 units

lesantik [10]

Answer:

288 pi or 904.22

Step-by-step explanation:

(4/3) × pi × r³

(4/3) × pi × 6³

288pi or

288 × 3.14 = 904.32 units³

7 0

3 years ago

Thompson and Thompson is a steel bolts manufacturing company. Their current steel bolts have a mean diameter of 144 millimeters,

kkurt [141]

Answer:

0.0524 = 5.24% probability that the sample mean would differ from the population mean by more than 2 millimeters.

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 establishes 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.

Mean diameter of 144 millimeters, and a variance of 49.

This means that $\mu = 144, \sigma = \sqrt{49} = 7$

Sample of 46:

This means that $n = 46, s = \frac{7}{\sqrt{46}}$

Wat is the probability that the sample mean would differ from the population mean by more than 2 millimeters?

Above 144 + 2 = 146 or below 144 - 2 = 142. Since the normal distribution is symmetric, these probabilities are equal, which means that we find one of them and multiply by two.

Probability the sample mean is below 142:

p-value of Z when X = 142, so:

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

By the Central Limit Theorem

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