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Aloiza [94]
4 years ago
6

11. The regression equation y=2x + 8 represents how many minutes a sound will last after applying x pounds of pressure to the sy

stem. If 4 pounds are applied, how long should we expect the sound to last.
Mathematics
1 answer:
Sidana [21]4 years ago
8 0
Then y=2(4)+8
          =8+8
          =16

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Find center,foci, and vertices of ellipse (x+3)^2/21+(y-5)^2/25=1
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I don't know if we can find the foci of this ellipse, but we can find the centre and the vertices. First of all, let us state the standard equation of an ellipse. 

(If there is a way to solve for the foci of this ellipse, please let me know! I am learning this stuff currently.) 

\frac{(x-x_{1})^2}{a^2}+ \frac{(y-y_{1})^2}{b^2}=1

Where (x_{1},y_{1}) is the centre of the ellipse. Just by looking at your equation right away, we can tell that the centre of the ellipse is: 

(-3,5)

Now to find the vertices, we must first remember that the vertices of an ellipse are on the major axis. 

The major axis in this case is that of the y-axis. In other words, 

b^2>a^2 

So we know that b=5 from your equation given. The vertices are 5 away from the centre, so we find that the vertices of your ellipse are: 

(-3,10)
 & (-3,0)

I really hope this helped you! (Partially because I spent a lot of time on this lol) 

Sincerely,

~Cam943, Junior Moderator
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Answer:

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Answer:

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Answer:

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In your own words, explain the Normal Distribution and provide a real world example.
elena-14-01-66 [18.8K]

Answer:

The Normal distribution is a continuous probability distribution with possible values all the reals. Some properties of this distribution are:

Is symmetrical and bell shaped no matter the parameters used. Usually if X is a random variable normally distributed we write this like that:

X \sim N(\mu , \sigma)

The two parameters are:

\mu who represent the mean and is on the center of the distribution

\sigma who represent the standard deviation  

One particular case is the normal standard distribution denoted by:

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Example: Usually this distribution is used to model almost all the practical things in the life one of the examples is when we can model the scores of a test. Usually the distribution for this variable is normally distributed and we can find quantiles and probabilities associated

Step-by-step explanation:

The Normal distribution is a continuous probability distribution with possible values all the reals. Some properties of this distribution are:

Is symmetrical and bell shaped no matter the parameters used. Usually if X is a random variable normally distributed we write this like that:

X \sim N(\mu , \sigma)

The two parameters are:

\mu who represent the mean and is on the center of the distribution

\sigma who represent the standard deviation  

One particular case is the normal standard distribution denoted by:

Z \sim N(0,1)

Example: Usually this distribution is used to model almost all the practical things in the life one of the examples is when we can model the scores of a test. Usually the distribution for this variable is normally distributed and we can find quantiles and probabilities associated

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4 years ago
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