Answer:
See picture and explanation below.
Step-by-step explanation:
With this information, the matrix A that you can find is the transformation matrix of T. The matrix A is useful because T(x)=Av for all v in the domain of T.
A is defined as ![T=([T(v_1)] [T(v_2] [T(v_3)])\text{ where }[T(v_i)]](https://tex.z-dn.net/?f=T%3D%28%5BT%28v_1%29%5D%20%5BT%28v_2%5D%20%5BT%28v_3%29%5D%29%5Ctext%7B%20where%20%7D%5BT%28v_i%29%5D)
denotes the vector of coordinates of 
respect to the basis 
(we can apply this definition because 
forms a basis for the domain of T).
The vector of coordinates can be computed in the following way: if 
then ![[T(v_i)]=(a_1,a_2,a_3)^t](https://tex.z-dn.net/?f=%5BT%28v_i%29%5D%3D%28a_1%2Ca_2%2Ca_3%29%5Et)
.
Note that we have all the required information: 
then ![[T(v_1)]=(0,1,0)^t](https://tex.z-dn.net/?f=%5BT%28v_1%29%5D%3D%280%2C1%2C0%29%5Et)
hence ![[T(v_2)]=[T(v_3)]=(1,0,0)^t](https://tex.z-dn.net/?f=%5BT%28v_2%29%5D%3D%5BT%28v_3%29%5D%3D%281%2C0%2C0%29%5Et)
The matrix A is on the picture attached, with the multiplication A(1,1,1).
Finally, to obtain the output required at the end, use the properties of a linear transformation and the outputs given:
In this last case, we can either use the linearity of T or multiply by A.
The answer is $132,000
First you multiply 120,000 by .10 which you get 12,000
Then you just add it and you find the answer
Answer:
i don't wanna tell u the wrong answer but I think it is A
Because it says 8 neclaces for EACH of her two friends
So i divided 11.52 by 16
So i got 0.72 I am sorry if it is wrong Have a great day!
Ummm i don't know what the pmf would be but the probability of grabbing a blue sock would be 10 out of 100...
Answer:
1. T test for independent means
2. T test for dependent means
3. T test for dependent means
Step-by-step explanation:
In number 1, the two groups are unrelated. The first group has 25 subjects and they're all unemployed. The second group has 24 subjects and their employment status is not stated and might not be the same all through. Also, the first group is receiving a new type of job skills program while the second group is taking the standard job skills program.
- The groups in the experiment are unrelated
- The tests in the research are unrelated
- The purpose of the research is unreasonable - the researcher seeks to measure how well all 49 subjects perform on 'a' job skills test! No comparison between the scores or mean scores of the two groups.
In number 2, the researcher uses the same subjects and also measures the same variable but twice. This is a good example of a study where the t test for dependent means can be taken. Same applies in case 3.
