26
3<span>⟌78
-6
-------
18
-18
-------
0
</span>
Answer:
The difference between the sample statistic and population parameter is called sampling error.
Step-by-step explanation:
We are given the following in the question:
- A sample is a part of population, it is a subset of population.
- A sample statistic describes the sample. It is a characteristic of sample and different from the population.
- A parameter describes the population. It is characteristic of a population.
- A sample may not be able to represent the whole population and this may lead to error.
- Thus, sampling error is the difference between the sample statistic and population parameter.
- It arises when the sample is not able to describe the population.
The difference between the sample statistic and population parameter is called sampling error.
Answer:
-72 i notice you're having trouble message me and ill help you
Answer:
1. ║u-z║= 5.66
2.║v-w║=6.0
3. ║w-u║=6.08
4.║v-u║=7.81
Step-by-step explanation:
The vectors are given as;
u = <-1, -3>, v = <5,-8>, w = <5, -2>, and z = <3, 1>.
To find the magnitude of the vectors;
1. ║u-z║
<-1 - 3> = <-4 and < -3 - 1> = <-4
║<-4,-4> ║= √{ -4²+-4²} = √32 = 5.66
2.║v-w║
<5,-8> - <5,-2>
<5-5> , <-8--2>
<0,-6>
║<0,-6>║= √{0²+ -6²} = √36 = 6
3. ║w-u║
<5,-2> - <-1,-3>
<5--1> , <-2--3>
<6,1>
║6,1║= √{6²+1²} = √36+1 = √37 = 6.08
4.║v-u║
<5,-8> - <-1,-3>
<5--1> , <-8--3>
< 6 , -5 >
║6,-5║= √{6²+-5²} = √36+25 =√61 = 7.81
