Answer:
1st,4th,5th option.
Step-by-step explanation:
Let evaluate each option.
A segment bisector is a line segment, ray, and/or line that bisects a line into two congruent parts. LM splits JK and KH into congruent parts. The first option is correct.
A perpendicular bisector is a line segment,ray and/or line that intersects a line segment,ray at a right angle. We don't have a perpendicular angle here and so that isn't a option.
M isn't a vertex of congruent angles as there is none in this figure.
The fourth and fifth option are correct. They both are on the segment bisector so they split the figure segments into two congruent parts. Since they are on the line segment and bisects it, they are considered the midpoint or middle point of the figure side.
Answer:
<em>The voltage at the middle source is</em> 
Step-by-step explanation:
<u>Voltage Sources in Series</u>
When two or more voltage sources are connected in series, the total voltage is the sum of the individual voltages of each source.
The figure shown has three voltage sources of values:



The sum of these voltages is:

Operating:

We know the total voltage is
, thus:

Equating the real parts and the imaginary parts independently:
4+a=6
1+b=-3
Solving each equation:
a = 2
b = -4
The voltage at the middle source is 
Answer:
Yes, this is A Linear Function!
Step-by-step explanation:
This is a linear function beacuse linear functions are straight lines on the graph as you may know. So when we graph these numbers it turns up as a straight increasing linear line.
(I attached a pic for u)
Hope this helps!
<3 me if it did!
Answer:
Is unbiased estimator
Step-by-step explanation:
In statistics, Numerical characteristics derived from population data is referred to as parameter, while those derived from the sample data are called statistic. When a sample is drawn from a particular population, the statistic of such sample could be used as either a point or interval estimate of the population. However, the estimator derived from the sample in most cases isn't equal to the exact parameter value. When this happens, that is, when population parameter equals the estimate of the sample statistic, then we have an unbiased estimator.