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ryzh [129]
3 years ago
8

HOW TO GRAPH x + 2y ≥ -6

Mathematics
1 answer:
Zolol [24]3 years ago
8 0

Answer:  The graph is attached (See explanation).

Step-by-step explanation:

The Slope-Intercept form of the equation of the line is:

y=mx+b

Where "m" is the slope and "b" is the y-intercept.

Given inequality:

x + 2y \geq  -6

You need to solve for "y":

2y \geq -x-6\\\\y\geq -\frac{1}{2}x-3

You can identify that the line is:

y= -\frac{1}{2}x-3

Which slope and y-intercept are:

m=-\frac{1}{2}\\\\b=-3

To find the x-intercept, substitute y=0 into the equation and solve for "x":

0= -\frac{1}{2}x-3\\\\3= -\frac{1}{2}x\\\\(3)(-2)=x\\\\x=-6

Then, you know that the line passes through the points (0,-3) and (-6,0), so you can graph it.

The symbol \geq indicates that the line is solid and you must shade the region above the line.

So, you get the graph attached.

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According to a report from a business intelligence company, smartphone owners are using an average of 22 apps per month. Assume
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Answer:

0.4332 = 43.32% probability that the sample mean is between 21 and 22.

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.

According to a report from a business intelligence company, smartphone owners are using an average of 22 apps per month.

This means that \mu = 22

Standard deviation is 4:

This means that \sigma = 4

Sample of 36:

This means that n = 36, s = \frac{4}{sqrt{36}}

What is the probability that the sample mean is between 21 and 22?

This is the p-value of Z when X = 22 subtracted by the p-value of Z when X = 21.

X = 22

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

By the Central Limit Theorem

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

Z = \frac{22 - 22}{\frac{4}{sqrt{36}}}

Z = 0

Z = 0 has a p-value of 0.5.

X = 21

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

Z = \frac{21 - 22}{\frac{4}{sqrt{36}}}

Z = -1.5

Z = -1.5 has a p-value of 0.0668.

0.5 - 0.0668 = 0.4332

0.4332 = 43.32% probability that the sample mean is between 21 and 22.

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