Answer:
Step-by-step explanation:
we have to orthonormalize the vectors:
According to Gram - Schmidt process, we have:
where,
The normalized vector is:
Now, the first step.
= u₁
Therefore, e₁ =
Now, we find e₂.
Therefore,
To find e₃:
So, we have the orthonormalized vectors .
Hence, the answer.
To find the orthonormal basis using the Gram-Schmidt process, we calculate the first vector by dividing the first given vector by its magnitude and normalize it. Then, we subtract the projection of each subsequent vector onto the previously found orthonormal vectors and normalize the resulting vector.
To find an orthonormal basis for the subspace of R4 spanned by the given vectors using the Gram-Schmidt process, we will start by finding the first vector of the orthonormal basis. Let's call the given vectors v1, v2, and v3, respectively. The first vector of the orthonormal basis, u1, is equal to v1 divided by its magnitude, which is ||v1||. So, u1 = v1 / ||v1||. We can calculate ||v1|| as √(1^2 + 0^2 + 1^2 + 1^2) = √3.
Therefore, u1 = (1/√3, 0/√3, 1/√3, 1/√3).
Now, we need to find u2, the second vector of the orthonormal basis. To do this, we subtract the projection of v2 onto u1 from v2, then divide the result by its magnitude. We calculate the projection of v2 onto u1 as proj_u1(v2) = u1 * dot(u1, v2), where dot(u1, v2) represents the dot product of u1 and v2.
Finally, we subtract proj_u1(v2) from v2 to get v2' = v2 - proj_u1(v2), and then normalize v2' to get u2 = v2' / ||v2'||.
We can repeat this process to find u3, the third vector of the orthonormal basis. Subtract proj_u1(v3) and proj_u2(v3) from v3, then normalize the result to get u3 = v3' / ||v3'||.
Therefore, the orthonormal basis for the subspace spanned by the given vectors is (1/√3, 0/√3, 1/√3, 1/√3), (0, 0, 0, 1), and (-1/√3, 0/√3, 1/√3, 1/√3).
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Answer:
7/12 of an hour
Step-by-step explanation:
you add them, by finding the common denominator.
1/3=4/12
1/4=3/12
3/12+4/12=7/12
Answer:
18-5i
Step-by-step explanation:
Answer: 12-i
12-(√-1)
Step-by-step explanation:
Original Question
Split
Solve for square root
Subtract
You can substitute for i
Substitute
Answer:
2
Step-by-step explanation:
Since the lines are parallel, then the slope of line B would be the same as line A.
Answer:
0.625
Step-by-step explanation:
15 divided by 24 which equals 0.625
Answer:
Therefore the radius of the can is 1.71 cm and height of the can is 2.72 cm.
Step-by-step explanation:
Given that, the volume of cylindrical can with out top is 25 cm³.
Consider the height of the can be h and radius be r.
The volume of the can is V=
According to the problem,
The surface area of the base of the can is =
The metal for the bottom will cost $2.00 per cm²
The metal cost for the base is =$(2.00× )
The lateral surface area of the can is =
The metal for the side will cost $1.25 per cm²
The metal cost for the base is =$(1.25× )
Total cost of metal is C= 2.00 +
Putting
Differentiating with respect to r
Again differentiating with respect to r
To find the minimize cost, we set C'=0
⇒r=1.71
Now,
When r=1.71 cm, the metal cost will be minimum.
Therefore,
⇒h=2.72 cm
Therefore the radius of the can is 1.71 cm and height of the can is 2.72 cm.
Answer:
0.0114
Step-by-step explanation:
(a) What is the probability of a fatal accident over a lifetime?
Suppose A be the event of a fatal accident occurring in a single trip.
Given that:
P(1 single auto trip in the United States result in a fatality) = P(A)
Then;
P(A) = 1/4011000
P(A) = 2.493 × 10⁻⁷
Now;
P(1 single auto trip in the United States NOT resulting in a fatality) is:
P() = 1 - P(A)
P() = 1 - 2.493 × 10⁻⁷
P() = 0.9999997507
However, P(fatal accident over a lifetime) = P(at least 1 fatal accident in lifetime i.e. 46000 trips)
= 1 - P(NO fatal accidents in 46000 trips)
Similarly,
P(No fatal accidents over a lifetime) = P(No fatal accident in the 46000 trips) = P(No fatality on the 1st trip and No fatality on the 2nd trip ... and no fatality on the 45999 trip and no fatality on the 46000 trip)
=
=
= 0.9885977032
Finally;
P(fatal accident over a lifetime) = 1 - 0.9885977032
P(fatal accident over a lifetime) = 0.0114022968
P(fatal accident over a lifetime) ≅ 0.0114