Answer:
x = -14
Step-by-step explanation:
Look at the image attatched. I have labeled the angles for better explanation.
We know that angle 1 is 54 degrees as is rests on a straight line with its adjacent angle at 126 degrees. This means that angle 1 would be 180 - 126 degrees, or 54 degrees. We also know that angle 1 and 3 must be congruent as the sides of the triangle opposite those angles are congruent as well. This means that both those angles are 54 degrees. Since the sum of all angles in a triangle must equal 180 degrees, we can get that angle 4 is 180 - (2*54) degrees, or 72. Since angle two and angle 4 both lie on a straight line, they must add up to 180 degrees. This means that the value of angle 2 would be 180 - 72, or 108 degrees. Since angle 2 is also equal to x+122, we get the equation:
108 = x + 122.
We then solve this by getting:
x = 108 - 122
which gives us the answer of
x = -14
Answer: pic of the question?
Step-by-step explanation:
Lets write this out:-
2.4 + 0.8 = ________ + 1.21 = ______ + 1.78 = ______ - 5.14 = _____
So to solve d blanks we will do d following:-
2.4 + 0.8 = 3.2
Now lets write this out AGAIN.
2.4 + 0.8 = 3.2 + 1.21 = ______ + 1.78 = ______ - 5.14 = ____
Now lets solve again:-
3.2 + 1.21 = 4.41
Now lets write this out AGAIN.
2.4 + 0.8 = 3.2 + 1.21 = 4.41 + 1.78 = ______ - 5.14 = ____
Now lets solve again:-
4.41 + 1.78 = 6.19
Now lets write this out AGAIN.
2.4 + 0.8 = 3.2 + 1.21 = 4.41 + 1.78 = 6.19 - 5.14 = ____
Now lets solve again:-
6.19 - 5.14 = 1.05
Now lets write this out AGAIN.
2.4 + 0.8 = 3.2 + 1.21 = 4.41 + 1.78 = 6.19 - 5.14 = 1.05
So, 2.4 + 0.8 = 3.2 + 1.21 = 4.41 + 1.78 = 6.19 - 5.14 = 1.05
Hope I helped ya!! xD
Answer:
(A) Set A is linearly independent and spans 
. Set is a basis for .
Step-by-Step Explanation
<u>Definition (Linear Independence)</u>
A set of vectors is said to be linearly independent if at least one of the vectors can be written as a linear combination of the others. The identity matrix is linearly independent.
<u>Definition (Span of a Set of Vectors)</u>
The Span of a set of vectors is the set of all linear combinations of the vectors.
<u>Definition (A Basis of a Subspace).</u>
A subset B of a vector space V is called a basis if: (1)B is linearly independent, and; (2) B is a spanning set of V.
Given the set of vectors ![A= \left(\begin{array}{[c][c][c][c]}1 & 0 & 0 & 0\\ 0 & 1 & 0 & 1\\ 0 & 0 & 1 & 1\end{array} \right)](https://tex.z-dn.net/?f=A%3D%20%5Cleft%28%5Cbegin%7Barray%7D%7B%5Bc%5D%5Bc%5D%5Bc%5D%5Bc%5D%7D1%20%26%200%20%26%200%20%26%200%5C%5C%200%20%26%201%20%26%200%20%26%201%5C%5C%200%20%26%200%20%26%201%20%26%201%5Cend%7Barray%7D%20%5Cright%29%20)
, we are to decide which of the given statements is true:
In Matrix ![A= \left(\begin{array}{[c][c][c][c]}(1) & 0 & 0 & 0\\ 0 & (1) & 0 & 1\\ 0 & 0 & (1) & 1\end{array} \right)](https://tex.z-dn.net/?f=A%3D%20%5Cleft%28%5Cbegin%7Barray%7D%7B%5Bc%5D%5Bc%5D%5Bc%5D%5Bc%5D%7D%281%29%20%26%200%20%26%200%20%26%200%5C%5C%200%20%26%20%281%29%20%26%200%20%26%201%5C%5C%200%20%26%200%20%26%20%281%29%20%26%201%5Cend%7Barray%7D%20%5Cright%29%20)
, the circled numbers are the pivots. There are 3 pivots in this case. By the theorem that The Row Rank=Column Rank of a Matrix, the column rank of A is 3. Thus there are 3 linearly independent columns of A and one linearly dependent column. has a dimension of 3, thus any 3 linearly independent vectors will span it. We conclude thus that the columns of A spans .
Therefore Set A is linearly independent and spans . Thus it is basis for .
