If you are asking what the square roots of 121 are and what the square roots of 49 are it is:
11^2=121 and
7^2=49
if, however you're asking what the square roots of 121 divided by 49, I don't know. (this sign '/' is commonly used as a division sign so I'd just want to clarify).
Answer:
<h2>16c² + 32cd + 16d²</h2>
Step-by-step explanation:
Area = (4c + 4d)×(4c + 4d)
= 16c² + 16cd + 16dc + 16d²
= 16c² + 32cd + 16d²
The simplified expression of 4x + 5xy - 2y is 4x(1 + y) + y(x - 2)
<h3>How to solve the expression?</h3>
The expression is given as:
4x + 5xy - 2y
The above expression cannot be solved.
However, the expression can be grouped
So, we have:
4x + 5xy - 2y
Rewrite 5xy as 4xy + xy
So, we have:
4x + 5xy - 2y = 4x + 4xy + xy - 2y
Factorize the expression
4x + 5xy - 2y = 4x(1 + y) + y(x - 2)
Hence, the simplified expression of 4x + 5xy - 2y is 4x(1 + y) + y(x - 2)
Read more about expressions at:
brainly.com/question/723406
#SPJ1
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:

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:

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:

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:

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
120+.5x=50+.7x
Subtract 50 from both sides and then subtract .5x from both sides to get 70=.2x. Then divide both sides by .2 to get x=350.