Answer:
I think the answer is (3,10) sorry if I got this wrong!
Step-by-step explanation:
In linear algebra, the rank of a matrix
A
A is the dimension of the vector space generated (or spanned) by its columns.[1] This corresponds to the maximal number of linearly independent columns of
A
A. This, in turn, is identical to the dimension of the vector space spanned by its rows.[2] Rank is thus a measure of the "nondegenerateness" of the system of linear equations and linear transformation encoded by
A
A. There are multiple equivalent definitions of rank. A matrix's rank is one of its most fundamental characteristics.
The rank is commonly denoted by
rank
(
A
)
{\displaystyle \operatorname {rank} (A)} or
rk
(
A
)
{\displaystyle \operatorname {rk} (A)}; sometimes the parentheses are not written, as in
rank
A
{\displaystyle \operatorname {rank} A}.
We can expand the logarithm of a product as a sum of logarithms:
Then using the change of base formula, we can derive the relationship
This immediately tells us that
Notice that none of 
can be equal to 1. This is because
for any choice of 
. This means we can safely do the following without worrying about division by 0.
so that
Similarly,
so that
So we end up with
###
Another way to do this:
Then
So we have
Answer:
The probability of eating pizza given that a new car is bought is 0.952
Step-by-step explanation:
This kind of problem can be solved using Baye’s theorem of conditional probability.
Let A be the event of eating pizza( same as buying pizza)
while B is the event of buying a new car
P(A) = 34% = 0.34
P(B) = 15% = 15/100 = 0.15
P(B|A) = 42% = 0.42
P(B|A) = P(BnA)/P(A)
0.42 = P(BnA)/0.34
P(B n A) = 0.34 * 0.42 = 0.1428
Now, we want to calculate P(A|B)
Mathematically;
P(A|B = P(A n B)/P(B)
Kindly know that P(A n B) = P(B n A) = 0.1428
So P(A|B) = 0.1428/0.15
P(A|B) = 0.952
The answer is D. 2x - 4/x^2- 4
