Answer: 122
Step-by-step explanation: Substitute the values of <em>x</em> and <em>y</em> into the expression.
![x^6+y^2 \\ \text{ is like } \\ ( )^6 + ( )^2](https://tex.z-dn.net/?f=x%5E6%2By%5E2%20%5C%5C%20%5Ctext%7B%20is%20like%20%7D%20%5C%5C%20%28%20%29%5E6%20%2B%20%28%20%29%5E2)
"Fill in the blanks" with the numbers given for <em>x</em> and <em>y</em>.
![(1)^6+(11)^2 = 1+121=122](https://tex.z-dn.net/?f=%281%29%5E6%2B%2811%29%5E2%20%3D%201%2B121%3D122)
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)](https://tex.z-dn.net/?f=%20X%20%5Csim%20N%28%5Cmu%20%2C%20%5Csigma%29)
The two parameters are:
who represent the mean and is on the center of the distribution
who represent the standard deviation
One particular case is the normal standard distribution denoted by:
![Z \sim N(0,1)](https://tex.z-dn.net/?f=Z%20%5Csim%20N%280%2C1%29)
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)](https://tex.z-dn.net/?f=%20X%20%5Csim%20N%28%5Cmu%20%2C%20%5Csigma%29)
The two parameters are:
who represent the mean and is on the center of the distribution
who represent the standard deviation
One particular case is the normal standard distribution denoted by:
![Z \sim N(0,1)](https://tex.z-dn.net/?f=Z%20%5Csim%20N%280%2C1%29)
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
Answer:
(1,-2)
Step-by-step explanation:
x= 1
y= 2
Answer:
D
Step-by-step explanation:
the pattern is -6 to get the next number