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
46, 16 is a little less than 1/2 of 34, so and 46 is a little less than 1/2 of 100.
Remember,
To subtract 2/3-1/2 you have to make them equivalent
2/3×2-1/2×3 = 4/6 - 3/6=
1/6
Answer:
A) 5x + 2y = 22
B) -2x + 6y = 3 We'll multiply A) by -3
A) -15x -6y = -66 Then we'll add B)
B) -2x + 6y = 3
-17x = -63
x = 3.7058823529
y = 1.7352941178
Step-by-step explanation: