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Pavel [41]
3 years ago
10

Which equations is enough information to prove that lines m and n are parallel lines cut by transversal? Check all that apply.

Mathematics
2 answers:
ollegr [7]3 years ago
7 0

Answer:

what are the equations given to you

Step-by-step explanation:


Elodia [21]3 years ago
4 0

Answer:

Step-by-step explanation:

m∠4 = 110° and m∠3 = 70°

m∠1 = 110° and m∠2 = 110°

m∠1 = 110° and m∠3 = 70°

m∠2 = 110° and m∠3 = 110°

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390, because 10% of 1300 is 130 so 130 times 3 = 390
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Nico wants to use a horizontal number line to compare 1 3/4
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1 3/4 is greater than 1.5.

Step-by-step explanation:

1. To make a line that measures 1 3/4, make 2 regular lines.

2. Divide one of the lines into 4 equal sections and erase the one section and leaving you with 1 3/4.

To make the 1.5:

1. Make a line and make another line but that is half of the length of the previous line.

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Public health officials claim that people living in low income neighborhoods have different Physical Activity Levels (PAL) than
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Answer:

The z-score for this data is Z = -0.26.

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.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean \mu = p and standard deviation s = \sqrt{\frac{p(1-p)}{n}}

This is based on knowledge that in the U.S., the mean PAL is 1.65 and the standard deviation is 0.55.

This means that \mu = 1.65, \sigma = 0.55

A study took a random sample of 51 people who lived in low income neighborhoods and found their mean PAL to be 1.63.

This means that n = 51, X = 1.63

Using a one-sample z test, what is the z-score for this data

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

By the Central Limit Theorem

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

Z = \frac{1.63 - 1.65}{\frac{0.55}{\sqrt{51}}}

Z = -0.26

The z-score for this data is Z = -0.26.

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Step-by-step explanation:

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