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slamgirl [31]
3 years ago
14

Urgent please help .On a piece of graph paper, graph y+2<-2/3x+4

Mathematics
1 answer:
Serjik [45]3 years ago
8 0
Take a look at the function y+2=- \frac{2}{3}x+4. You can simplify it to y=- \frac{2}{3}x+2. If x=0, then y=2 and when y=0, x=3. You obtain two points (0,2) and (3,0) that lie on the line y+2=- \frac{2}{3}x+4.

Since y+2\le - \frac{2}{3}x+4, the line y+2=- \frac{2}{3}x+4 should belong to the shaded area. 

Now take point (0,0). Since 0+2\le- \frac{2}{3}\cdot 0+4, you can conclude that point (0,0) belongs to the shaded area.Using all these thoughts, you can make a conclusion that the correct choice is B.



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The mean per capita consumption of milk per year is 131 liters with a variance of 841. If a sample of 132 people is randomly sel
Inessa [10]

Answer:

0.8389 = 83.89% probability that the sample mean would be less than 133.5 liters.

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.

The mean per capita consumption of milk per year is 131 liters with a variance of 841.

This means that \mu = 131, \sigma = \sqrt{841} = 29

Sample of 132 people

This means that n = 132, s = \frac{29}{\sqrt{132}}

What is the probability that the sample mean would be less than 133.5 liters?

This is the p-value of Z when X = 133.5. So

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

By the Central Limit Theorem

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

Z = \frac{133.5 - 131}{\frac{29}{\sqrt{132}}}

Z = 0.99

Z = 0.99 has a p-value of 0.8389

0.8389 = 83.89% probability that the sample mean would be less than 133.5 liters.

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Answer:

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Step-by-step explanation:

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Varvara68 [4.7K]
 To get the answer do this: 

2.5% of what is 2.21

2.5%x = 2.21

2.5/100x = 2.21

0.025x = 2.21

divide both sides by 0.025

0.025x/0.025 = 2.21/0.025

x = 88.4
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Four equations in the options.

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From the given options, only option B, i.e., y=\dfrac{1}{4}x, is of the y=kx, where, k=\dfrac{1}{4}.

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