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Test your basic knowledge |
CSET Linear Algebra
Start Test
Study First
Subjects
:
cset
,
math
,
algebra
Instructions:
Answer 44 questions in 15 minutes.
If you are not ready to take this test, you can
study here
.
Match each statement with the correct term.
Don't refresh. All questions and answers are randomly picked and ordered every time you load a test.
This is a study tool. The 3 wrong answers for each question are randomly chosen from answers to other questions. So, you might find at times the answers obvious, but you will see it re-enforces your understanding as you take the test each time.
1. Two vectors are parallel if their components are multiples of each other. Ex. <2 -5> and <4 -10> are because 2(2 -5)= 4 -10
orthogonal vectors
Opposite vectors
dot product
Parallel vectors
2. Take the magnitude of the cross product of any two adjacent vectors of the form <a - b - c>(a - and b are y - y - x-x - and c can be zero)
vector subtraction
Fundamental theorem of arithmetic
area of a parallelogram
Perfect numbers
3. On X - Y and Z plane
unit vector
Equivalent vectors
3- dimensional vectors
Scalar multiple
4. Can multiple a vector by a scalar. components of vectors are the same - magnitude is IkI times the vector - direction depends on if k is pos. or neg
Opposite vectors
Scalar multiple
Vector addition
Inverse matrices
5. F ? is the angle between vector A? and the x- axis - then Ax=Acos??Ay=Asin?? EX. If ?= 60
parallelogram law
divisibility rule for 3
Triangle (head to tail) law
angle of vector
6. Show statement is true for n=1 - then show it is ture for K+1
3- dimensional vectors
orthogonal vectors
divisibility rule for 3
To prove by mathematical induction
7. Equals the magnitude of the cross product
Multiplying matrices
Perfect numbers
Area of a parallelogram
unit vector
8. Dot product must equal zero
Equivalent vectors
dot product
orthogonal vectors
dot product definition
9. Sum of numbers divisible by three - number is divisible by 3.
unit vector
divisibility rule for 3
Magnitude of a vector
Finding GCD
10. |A|=Ax2+Ay2 ?=tan -1(Ay/Ax)
To prove by mathematical induction
Pascals rule
If you know the x and Y component of a vector
area of a parallelogram
11. If a? and b? are vectors and ? is the angle between them - the dot product denoted by a?
Finding GCD
Addition
Angle of dot product
If you know the x and Y component of a vector
12. Every integer greater than 1 can be expressed as product of prime numbers
Area of a parallelogram
Vector has two things
orthogonal vectors
Fundamental theorem of arithmetic
13. To find the minor of an element in a matrix - take the determinant of the part of the matrix without that element.
vector subtraction
Algebraic vector ordered pair
Minors
polygon law of vector addition
14. Vector a +vector b is placing head of a next to tail of b and sum is a new vector
angle of vectors using cross product:
polygon law of vector addition
Algebraic vector ordered pair
Triangle (head to tail) law
15. Or norm - of a vector using the distance formula. |v|=(x2-x1)2+(y2- y1)2. (square each component of vector)
angle of vectors using cross product:
Opposite vectors
Magnitude of a vector
Velocity vector
16. (mk) + (mk -1)= (m+1k)
How many primes to check for?
Perfect numbers
Pascals rule
divisibility rule for 3
17. Same as triangle law except resultant vector is a diagonal of a parallelogram
dot product definition
angle of vector
parallelogram law
area of a parallelogram
18. Is commutative - associative
Finding GCD
Addition
Parallel vectors
Angle of dot product
19. |a?xb?|=|a?||b?|sin? | = | a?. ? is the angle between a? and b? and is restricted to be between 0
area of a parallelogram
Inverse matrices
Triangle (head to tail) law
angle of vectors using cross product:
20. Divisible by 2 and 3
Multiplying matrices
divisibility rule for 6
zero vector
Scalar multiple
21. Matrix 3x3: i j k a1 a2 a3 b1 b2 b3 i (a2a3/b2b3) - j(a1a3/b1b3) + k (a1a2/b1b2)= <i - j - k>
parallel vectors
Magnitude of a vector
polygon law of vector addition
Cross product
22. Multiply first row by first column - add. Multiply first row by second column - add. Mxn multiply by next. Not necessarily commutative
zero vector
Multiplying matrices
Magnitude of a vector
angle of vectors using cross product:
23. Switch the direction of one vector and add them (tail to head)
3- dimensional vectors
vector subtraction
polygon law of vector addition
Vector has two things
24. Numbers that are a sum of all of their factors. 6 - 8 - 128
Equivalent vectors
Finding GCD
Multiplying matrices
Perfect numbers
25. Have same magnitude and direction - but possibly different starting points
Minors
zero vector
polygon law of vector addition
Equivalent vectors
26. Sum of last two digit divisible by 4
dot product
If you know the x and Y component of a vector
divisibility rule for 4
Velocity vector
27. (0 -0) in two dimensions - (0 -0 -0) in three. magnitude is 0 and no direction - it is a point geometrically
Inverse matrices
Addition
zero vector
divisibility rule for 3
28. Must be scalar multiples of each other
How many primes to check for?
Multiplying matrices
parallel vectors
divisibility rule for 3
29. Magnitude and direction
Equivalent vectors
Vector has two things
Opposite vectors
If you know the x and Y component of a vector
30. (inner product)(scalar product) Result is scalar - large if vectors parallel - 0 if vectors perpendicular. Tells us how close vectors are pointing to same point.
Scalar multiple
Angle of dot product
divisibility rule for 4
dot product
31. Addition: A?+B?=<x1+x2 - y1+y2>or C?+D?=<x1+x2 - y1+y2 -z1+z2> Subtraction: A?- B?=<x1-x2 - y1- y2>or C?+D?=<x1-x2 - y1- y2 -z1-z2> Scalar Multiplication: kC?=k<x1 - y1 -z1>=<kx1 - ky1 - kz1>or kA?=k<x1 - y1>=<kx1 - ky1>
parallel vectors
Minors
parallelogram law
algebraic vector operations
32. Does not matter what order you add them in - it will result in straight vector. If (n -1) numbers of vectors are represented by n -1 sides of a polygon - then the nth side is the sum of the vectors
Scalar multiple
Least common multiple
polygon law of vector addition
3- dimensional vectors
33. If the GCF is one - the numbers are relatively prime
Cross product
Relatively prime
Equivalent vectors
orthogonal vectors
34. Product of two numbers divided by greatest common denominator
Opposite vectors
Least common multiple
algebraic vector operations
divisibility rule for 3
35. A vector with a magnitude of 1. the positive X- axis is vector i - pos. <1 -0> y xis is vector j <0 -1>
dot product
Area of a parallelogram
unit vector
Vector has two things
36. Square matrix with ones diagonally and zeros for the rest.
Cross product
Identity matrix
Area of a parallelogram
Opposite vectors
37. If a? and b? are two vectors - <a1 - a2> and <b1 - b2> - the dot product of a?and b? is defined as a?
Triangle (head to tail) law
Cross product
dot product definition
unit vector
38. Follows same rules as scalar - but done component by component - and produces another vector (resultant)
parallel vectors
Multiplying matrices
Vector addition
Identity matrix
39. Vectors with same magnitude but are in opposite directions (+?-)
Fundamental theorem of arithmetic
Opposite vectors
Velocity vector
divisibility rule for 6
40. If the initial point of a vector has coordinate (x1 - y1)and the terminal point has coordinate (x2 - y2) - then the ordered pair that represents the vector is <x2-x1 - y2- y1>> .
Algebraic vector ordered pair
Vector addition
divisibility rule for 6
Parallel vectors
41. Divide bigger by smaller - dividing smaller by remainder - first remainder by second - second by third - until you have a remainder of 0. Last remainder is GCD (aka euclidean algorithm)
dot product definition
Finding GCD
divisibility rule for 3
How many primes to check for?
42. Check for up to the square root of the number
How many primes to check for?
If you know the x and Y component of a vector
Fundamental theorem of arithmetic
Identity matrix
43. Vector that describes direction and speed
Velocity vector
Algebraic vector ordered pair
Vector has two things
dot product
44. A matrix that can be multiplied by the original to get the identity matrix
If you know the x and Y component of a vector
Identity matrix
Inverse matrices
parallel vectors