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BaLLatris [955]
3 years ago
5

Solve for x (round to the nearest thousandth)

Mathematics
1 answer:
tamaranim1 [39]3 years ago
4 0

Answer:

Step-by-step explanation:

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15 POINTS IF YOU CAN ANSWER THIS CORRECTLY!!!
My name is Ann [436]

4√2x−8+4√2x+8=0

Simplifies to:

11.313708x=0

Let's solve your equation step-by-step.

11.313708x=0

Step 1: Divide both sides by 11.313708.

<u>11.313708x </u>

11.313708

=

<u>       0        </u>

11.313708

x=0

Answer:

x=0

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4 years ago
Julie bought 5 bottles of water for $5.35. Which of the following have the same unit rate? (Click all that apply.)
Dafna1 [17]
I feel that the answer is A.

6 0
3 years ago
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Anyone............I will give BRAINLIEST​
posledela

Answer:

  • 100 cm²

Step-by-step explanation:

<u>Area of the larger circle:</u>

  • A = π(2r)² = 4πr²

<u>The shaded area:</u>

  • π(2r)² - πr² = 75
  • 3πr² = 75
  • πr² = 25

<u>Area of the larger circle:</u>

  • A = 4(25) = 100 cm²
6 0
3 years ago
Tony has $64.29 in his wallet before he buys a DVD for $14.99.
nlexa [21]
C) 49.30


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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:

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

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

4 0
3 years ago
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