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klasskru [66]
3 years ago
9

Draw a number line -5 through 5 and mark 2x<6

Mathematics
1 answer:
inna [77]3 years ago
8 0

Answer:

x < 3

Step-by-step explanation:

Before number line can be drawn, there is need to find the value of x in the inequality given. Thus,

2x < 6

Divide both sides by 2

\frac{2x}{2}  <  \frac{6}{2}

x < 3

The number line is indicated in the attached picture.

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Suppose monthly rental prices for a one-bedroom apartment in a large city has a distribution that is skewed to the right with a
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Answer:

a) Nothing, beause the distribution of the monthly rental prices are not normal.

b) 1.43% probability that the sample mean rent price will be greater than $900

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}}

(a) Suppose a one-bedroom rental listing in this large city is selected at random. What can be said about the probability that the listed rent price will be at least $930?

Nothing, beause the distribution of the monthly rental prices are not normal.

(b) Suppose a random sample 30 one-bedroom rental listing in this large city will be selected, the rent price will be recorded for each listing, and the sample mean rent price will be computed. What can be said about the probability that the sample mean rent price will be greater than $900?

Now we can apply the Central Limit Theorem.

\mu = 880, \sigma = 50, n = 30, s = \frac{50}{\sqrt{30}} = 9.1287

This probability is 1 subtracted by the pvalue of Z when X = 900.

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

By the Central Limit Theorem

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

Z = \frac{900 - 880}{9.1287}

Z = 2.19

Z = 2.19 has a pvalue of 0.9857

1 - 0.9857 = 0.0143

1.43% probability that the sample mean rent price will be greater than $900

8 0
3 years ago
4. The figures below are similar. What is
RideAnS [48]

Answer:

20 but I am not sure.....

4 0
3 years ago
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The graph of function p is shown on the grid. The coordinates of the x-intercepts, the y-intercepts, and the vertex are integers
Aleks [24]

Answer: I even

Step-by-step explanation: I am so so sorry for the Chinook ethat and I have don’t

Know how the sun goes out for a while and I don’t want to you say that again lol lol you

8 0
3 years ago
A ferry will safely accommodate 82 tons of passenger cars. Assume that the meanweight of a passenger car is 2 tons with standard
Shalnov [3]

Answer:

The probability that the maximum safe-weight will be exceeded is <u>0.0455 or 4.55%</u>.

Step-by-step explanation:

Given:

Maximum safe-weight of 37 cars = 82 tons

∴ Maximum safe-weight of 1 car (x) = 82 ÷ 37 = 2.22 tons (Unitary method)

Mean weight of 1 car (μ) = 2 tons

Standard deviation of 37 cars = 0.8 tons

So, standard deviation of 1 car is given as:

\sigma=\frac{0.8}{\sqrt{37}}=0.13

Probability that maximum safe-weight is exceeded, P(x > 2.22) = ?

The sample is normally distributed (Assume)

Now, let us determine the z-score of the mean weight.

The z-score is given as:

z=\frac{x-\mu}{\sigma}\\\\z=\frac{2.22-2}{0.13}\\\\z=\frac{0.22}{0.13}=1.69

Now, finding P(x > 2.22) is same as finding P(z > 1.69).

From the z-score table of normal distribution curve, the value of area under the curve for z < 1.69 is 0.9545.

But we need the area under the curve for z > 1.69.

So, we subtract from the total area. Total area is 1 or 100%.

So, P(z > 1.69) = 1 - P(z < 1.69)

P(z>1.69)=1-0.9545=0.0455\ or\ 4.55\%

Therefore, the probability that the maximum safe-weight will be exceeded is 0.0455 or 4.55%.

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3 years ago
A survey,45% of respondents said they own a DVD player.Based on this information,predict how many of the 9,985 residents of Sadi
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Answer:

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Step-by-step explanation:

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