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2 years ago

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The Masons are driving home from a trip. The function graphed models the Masons' distance from home, y, in miles, after x hours

of driving.
What do the key features of the graph indicate in this situation?

Drag and drop the answers into the boxes.

2 answers:

ikadub [295]2 years ago

8 0

ANSWER

The key features are:

1. The y-intercept which is $(0,400)$ .

This means that at time $x=0$ , the Masons are $400$ miles away from home.

2. The <em>x-intercept</em> which is $(8,0)$ .

This means after $8$ hours the Masons reached home.

The reason is that $y=0$ miles. This means that there is no distance between the Masons and their home.

3. The slope of the graph which is $\frac{distance}{time}$ tells us the speed at which they travel towards their home.

$Speed=|\frac{0-400}{8-0}| =|-50|=50$ .

This means they traveled at a speed of $50miles/hour$ .

The negative slope of the graph tell us that the distance is reducing as they approach their home.

Paha777 [63]2 years ago

5 0

You have everything right. If you look, it says Y is distance from home, and X is the time they spent driving.
I took the test and made a 100%

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2 years ago

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Answer:

There is a 99.24% probability that Claude's sample has a mean between 119.985 and 120.0125 inches.

Step-by-step explanation:

The Central Limit Theorem estabilishes that, for a random variable X, with mean $\mu$ and standard deviation $\sigma$ , a large sample size can be approximated to a normal distribution with mean $\mu$ and standard deviation $\frac{\sigma}{\sqrt{n}}$ .

Problems of normally distributed samples can be 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:

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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.

In this problem, we have that:

The population of rods has a mean length of 120 inches and a standard deviation of 0.05 inch. This means that $\mu = 120, \sigma = 0.05$ .

Claude Ong, manager of Quality Assurance, directs his crew measure the lengths of 100 randomly selected rods. This means that $n = 100, s = \frac{\sigma}{\sqrt{n}} = \frac{0.05}{\sqrt{100}} = 0.005$ .

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We are working with the sample mean, so we use the standard deviation of the sample, that is, $s$ instead of $\sigma$ in the z score formula.

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Source:
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