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kow [346]
2 years ago
14

A chalk board’s dimensions have an

Mathematics
1 answer:
Wewaii [24]2 years ago
7 0

Step-by-step explanation:

5:3=35

5=35×3

5=105

5÷105=0.05

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What are the transformations?<br> y=(x-2) +4
DaniilM [7]

Answer:

The horizontal shift depends on the value of h h. The horizontal shift is described as: g(x) = f (x+h) g ( x) = f ( x + h) - The graph is shifted to the left h h units. g(x) = f (x−h) g ( x) = f ( x - h) - The graph is shifted to the right h h units. The vertical shift depends on the value of k k.

Step-by-step explanation:

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The blue segment below is a radius of oo. What is the length of the diameter of the circle?
galina1969 [7]

Answer:

<h2>Diameter = 25.4 units</h2>

<u>Step-by-step explanation:</u>

radius = 12.7

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= 2 × 12.7

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3 years ago
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HELP ME ASAP
Komok [63]

B:

Step-by-step explanation

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3 years ago
What is the answer ?
pentagon [3]

Answer:

in order for your fraction to equal 3 you need to have 9/3 which will equal 3. so what minus 1 will get you 9? 10 will. x=10

10-1/3

9/3

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3 years ago
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Consider a parent population with mean 75 and a standard deviation 7. The population doesn’t appear to have extreme skewness or
Aleks04 [339]

Answer:

a) \bar X \sim N(\mu=375, \sigma={\bar X}=\frac{7}{\sqrt{40}}=1.107)

b) Since the sample size is large enough n>30 and the original distribution for the random variable X  doesn’t appear to have extreme skewness or outliers, the distribution for the sample mean would be bell shaped and symmetrical.

c) P(\bar X \leq 77)=P(Z

d) See figure attached

Step-by-step explanation:

Previous concepts

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".  

The central limit theorem states that "if we have a population with mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement, then the distribution of the sample means will be approximately normally distributed. This will hold true regardless of whether the source population is normal or skewed, provided the sample size is sufficiently large".

Let X the random variable of interest. We know from the problem that the distribution for the random variable X is given by:

E(X) = 75

sd(X) = 7

We take a sample of n=40 . That represent the sample size

Part a

From the central limit theorem we know that the distribution for the sample mean \bar X is also normal and is given by:

\bar X \sim N(\mu, \frac{\sigma}{\sqrt{n}})

\bar X \sim N(\mu=375, \sigma={\bar X}=\frac{7}{\sqrt{40}}=1.107)

Part b

Since the sample size is large enough n>30 and the original distribution for the random variable X  doesn’t appear to have extreme skewness or outliers, the distribution for the sample mean would be bell shaped and symmetrical.

Part c

In order to answer this question we can use the z score in order to find the probabilities, the formula given by:

z=\frac{\bar X- \mu}{\frac{\sigma}{\sqrt{n}}}

And we want to find this probability:

P(\bar X \leq 77)=P(Z

We can us the following excel code: "=NORM.DIST(1.807,0,1,TRUE)"

Part d

See the figure attached.

8 0
3 years ago
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