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marishachu [46]
3 years ago
9

The length of an object's shadow varies directly with It's heigt. If a can is 13 cm tall casts a shadow that is 7.5 cm long, a b

ottle that is 2.5 cm tall will cast a shadow that is approximately 14.2 cm long.
Mathematics
1 answer:
svetoff [14.1K]3 years ago
6 0
X = Can/Bottle height, y = Shadow length
x = 13 cm, y = 7.5 cm
x = 2.5 cm, y = 14.2 cm
I'm assuming your question is asking for an equation to model this. Since there are only two data points the only equation that can be made is linear
y = mx + c
m = (y2 - y1)/(x2 - x1) <- Let 14.2 be y2, and 2.5 be x2 (it is important)
m = (14.2 - 7.5)/(2.5 - 13)
m = 6.7/-10.5
m = -0.638
y = -0.638x + c
To find c we can sub any one of the two coordinates, 
i'm choosing (2.5,14.2)
14.2 = -0.638(2.5) + c
14.2 = -1.595 + c
14.2 + 1.595 = c
15.795 = c
So the final equation is y = -0.638x + 15.795
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85.31% probability that their mean rebuild time exceeds 8.1 hours.

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 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 random variable X, with mean \mu and standard deviation \sigma, the sample means with size n of at least 30 can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}

In this problem, we have that:

\mu = 8.4, \sigma = 1.8, n = 40, s = \frac{1.8}{\sqrt{40}} = 0.2846

If 40 mechanics are randomly selected, find the probability that their mean rebuild time exceeds 8.1 hours.

This is 1 subtracted by the pvalue of Z when X = 8.1. So

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

By the Central Limit Theorem

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

Z = \frac{8.1 - 8.4}{0.2846}

Z = -1.05

Z = -1.05 has a pvalue of 0.1469

1 - 0.1469 = 0.8531

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