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belka [17]
2 years ago
6

How is copying segment similar to copying an angle ?

Mathematics
1 answer:
pochemuha2 years ago
3 0

Answer:

Copying a line segment or angle is an illustration of transformation. Both are similar, because they are both rigid transformation.

When an angle is copied to a new angle, the new angle and the old angle will have the same measure

Similarly;

When a line segment is copied to a new segment, the new line segment and the old line segment will have the same measure

This type of transformation is referred to as a rigid transformation.

Hence, copying a line segment is similar to copying an angle, because they are both rigid transformations

Step-by-step explanation:

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13

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If there are 1000 grams in a kilogram in 454 grams in a pound how many pounds are there in a kilogram?
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2.2

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4 years ago
Consider the probability that greater than 96 out of 153 DVDs will work correctly. Assume the probability that a given DVD will
ICE Princess25 [194]

Answer:

0.3594 = 35.94% probability that greater than 96 out of 153 DVDs will work correctly.

Step-by-step explanation:

Binomial probability distribution

Probability of exactly x sucesses on n repeated trials, with p probability.

Can be approximated to a normal distribution, using the expected value and the standard deviation.

The expected value of the binomial distribution is:

E(X) = np

The standard deviation of the binomial distribution is:

\sqrt{V(X)} = \sqrt{np(1-p)}

Normal probability distribution

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:

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.

When we are approximating a binomial distribution to a normal one, we have that \mu = E(X), \sigma = \sqrt{V(X)}.

In this problem, we have that:

n = 153, p = 0.62

So

\mu = E(X) = np = 153*0.62 = 94.86

\sigma = \sqrt{V(X)} = \sqrt{np(1-p)} = \sqrt{153*0.62*0.38} = 6

Probability that greater than 96 out of 153 DVDs will work correctly.

97 or more DVDs, which is 1 subtracted by the pvalue of Z when X = 97. So

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

Z = \frac{97 - 94.86}{6}

Z = 0.36

Z = 0.36 has a pvalue of 0.6406

1 - 0.6406 = 0.3594

0.3594 = 35.94% probability that greater than 96 out of 153 DVDs will work correctly.

3 0
3 years ago
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