Answer:
Hello!!! Princess Sakura here ^^
Step-by-step explanation:
It is
because you should use
then just plug it in using
(1, 4) and (-2, -2).

That eliminates everything except the second one and the third.
So now we would find the b in the equation 

and that's all
9514 1404 393
Answer:
(d) A = 14.28 in², P = 14.28 in
Step-by-step explanation:
The figure is wholly contained within a 4" square, which has an area of (4 in)² = 16 in², and a perimeter of 4(4 in) = 16 in. Since the figure is smaller in area and has a shorter perimeter (the top corners are rounded, not square), both answer values must be less than 16.
The only reasonable choice is the last choice: 14.28 in², 14.28 in.
__
If you want to figure this out in detail, you have the area of a rectangle that is 2 in by 4 in, and the area of a semicircle of radius 2 in. The total area is ...
A = LW +1/2πr²
A = (2 in)(4 in) + 1/2(3.14)(2 in)² = 8 in² +6.28 in²
A = 14.28 in²
__
The perimeter is half that of a 4" square, plus half that of a 4" circle.
P = 1/2(4(4 in) +π(4 in)) = (2 in)(4 +π) = 2(7.14) in
P = 14.28 in
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
Answer:
sorry don’t understand it’s all close together
Step-by-step explanation: