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s344n2d4d5 [400]
3 years ago
7

What would be the TSA (Total Surface Area)?

Mathematics
1 answer:
bekas [8.4K]3 years ago
3 0

Answer:

B (133 square meters)

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In a batch of 890 calculators, 12 were found to be defective. What is the probability that a calculator chosen at random will be
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Answer:

<em>1.3%</em>

When entered into a calculator, 12/890 (the chance of a given calculator being defective) = 0.01348...

As a percent this is 100*0.01348% = 1.348%, and to the nearest tenth, 1.3%

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Step-by-step explanation:

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Jules wants to put a fence around his backyard. What is the perimeter of his backyard?​
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a vehicle uses 2 1/8 gallon of gasoline to travel 12 3/4 miles. At this rate, how many miles can the vehicle travel per gallon
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The number of cars running a red light in a day, at a given intersection, possesses a distribution with a mean of 2.4 cars and a
liberstina [14]

Answer:

The sampling distribution of the sample mean is:

\bar X\sim N(\mu_{\bar x}=2.4,\ \sigma_{\bar x}=0.40)

Step-by-step explanation:

According to the Central Limit Theorem if we have a population with mean <em>μ</em> and standard deviation <em>σ</em> and appropriately huge random samples (<em>n</em> > 30) are selected from the population with replacement, then the distribution of the sample mean will be approximately normally distributed.

Then, the mean of the distribution of sample means is given by,

\mu_{\bar x}=\mu

And the standard deviation of the distribution of sample means is given by,

\sigma_{\bar x}=\frac{\sigma}{\sqrt{n}}

Let <em>X</em> = number of cars running a red light in a day, at a given intersection.

The information provided is:

E(X)=\mu=2.4\\SD(X)=\sigma=4\\n=100

The sample selected is quite large, i.e. <em>n</em> = 100 > 30.

The Central limit theorem can be used to approximate the sampling distribution of the sample mean number of cars running a red light in a day, by the Normal distribution.

The mean of the sampling distribution of the sample mean is:

\mu_{\bar x}=\mu=2.4

The standard deviation of the sampling distribution of the sample mean is:

\sigma_{\bar x}=\frac{\sigma}{\sqrt{n}}=\frac{4}{\sqrt{100}}=0.40

The sampling distribution of the sample mean is:

\bar X\sim N(\mu_{\bar x}=2.4,\ \sigma_{\bar x}=0.40)

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3 years ago
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