Answer:
a) False
b) False
c) True
d) False
e) False
Step-by-step explanation:
a. A single vector by itself is linearly dependent. False
If v = 0 then the only scalar c such that cv = 0 is c = 0. Hence, 1vl is linearly independent. A set consisting of a single vector v is linearly dependent if and only if v = 0. Therefore, only a single zero vector is linearly dependent, while any set consisting of a single nonzero vector is linearly independent.
b. If H= Span{b1,....bp}, then {b1,...bp} is a basis for H. False
A sets forms a basis for vector space, only if it is linearly independent and spans the space. The fact that it is a spanning set alone is not sufficient enough to form a basis.
c. The columns of an invertible n × n matrix form a basis for Rⁿ. True
If a matrix is invertible, then its columns are linearly independent and every row has a pivot element. The columns, can therefore, form a basis for Rⁿ.
d. In some cases, the linear dependence relations among the columns of a matrix can be affected by certain elementary row operations on the matrix. False
Row operations can not affect linear dependence among the columns of a matrix.
e. A basis is a spanning set that is as large as possible. False
A basis is not a large spanning set. A basis is the smallest spanning set.
Answer:
(2,0)
Step-by-step explanation:
Simply plug in the coordinates. y= 3x - 6, so in this case 0= 3(2) - 6 or 0=0, making the point on the line. If the equation is not true like when using (0,3) and getting 3= -6, then the point is not on the line.
It isn't proportional because 3/4 is proportional to 9/16 not 9/15.
Answer:
My guy, it's C...
Step-by-step explanation:
U asked this already XD
Answer:
x + 6 =
Step-by-step explanation:
In math sum means addition, difference is subtraction, product is multiplication, and quotient is division
