Answer: he has 128 + d
Step-by-step explanation:
well if he had 128 yesterday and today he got d more just add d to 128 and ull see
for example, lets say d = 16
to find out the total we woukd have to add 16 to 128 (just an example the answer is not d=16)
answer= 128+d
Simplify the experssion and you get 10.
Hope this helps!
Well if you have 60 and she has 120 i will set it out as a sequence week by week
60,67,74,81,88,95,102,109,116,123,130,137,144,151,158,165,172,179,186,193,200,207,214,221,228,235,242,249,256,263,270
120,125,130,135,140,145,150,155,160,165,170,175,180,185,190,195,200,205,210,215,220,225,230,235,240, 245,250,255,260,265,270
it would take 31 weeks and the total is 270
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.