Answer:
$1769.06
Step-by-step explanation:
The sum of Mia's three highest salaries is ...
$92,000 +94,800 +96,250 = $283,050
so the average is ...
$283,050/3 = $94,350
Her pension is then ...
0.01875 × $94,350 = $1769.06
_____
<em>Additional comment</em>
This is equivalent to the total of those salaries, divided by 160.
T/3 × 0.01875 = T × (0.01875/3) = T × 0.00625 = T/160
Sometimes, there are simpler ways to calculate things like this.
Answer:
4/5
Step-by-step explanation:
<u>Given</u>,
Area of the triangle = 1/4 square meters
From the diagram,
Height = 2/5 m
<u>To find</u> : Length of the base
<u>Formula</u> : -
A = bh/2
Here,
A denotes Area
b denotes Base
h denotes Height
A = 1/4
h = 2/5
A = bh/2
Cross multiply,
A * 2 = bh
2A = bh
2 * (1/4) = b * (2/5)
(1 * 2)/4 = (b * 2)/5
2/4 = 2b/5
1/2 = 2b/5
Cross multiply,
1 * 5 = 2 * 2b
5 = 4b
b = 4/5 meters
Hence,
The length of the base is 4/5 meters.
So if boys is 6 and girls is 15 it would be 6/15, but that can be simplified to 2/5.
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