SPSU Math 1113: Precalculus Cheat Sheet
tan'2α+ =
%& '.+
#2%& 3 '.+
§5.1 Polynomial Functions and Models (review)
Steps to Analyze Graph of Polynomial
sin = ±5 cos = ±5
1. y-intercepts: f (0) 4 #2 '4+ 4 #6 '4+
2. x-intercept: f(x) = 0
tan = ±5 = =
3. f crosses / touches axis @ x-intercepts 4 #2 '4+ #2 4 4
#6 '4+ 4 #6 4
4. End behavior: like leading term
= =
5. Find max num turning pts of f: (n – 1) 7 8 9
:
6. Behavior near zeros for each x-intercept §9.2 Law of Sines
7. May need few extra pts to draw fcn.
§9.3 Law of Cosines a2 = b2 + c2 – 2bc cos A
§5.2 Rational Functions 2 2 2
c = a + b – 2ab cos C b2 = a2 + c2 – 2ac cos B
Finding Horizontal/Oblique Asymptotes of R
where degree of numer. = n and degree of denom. = m
;< sin = = >< sin ? = >; sin @
# # #
§9.4 Area of Triangle
2. If n = m, line = is a horizontal asymptote.
1. If n < m, horizontal asymptote: y = 0 (the x-axis).
K=
A= '> + ; + <+
#
Heron’s Formula
K = CA 'A − >+'A − ;+'A − <+
3. If n = (m + 1), quotient from long div is ax + b and line y = ax
+ b is oblique asymptote.
4. If n > (m + 1), R has no asymptote.
§9.5 Simple & Damped Harmonic Motion
§7.6 Graphing Sinusoidals Simple Harmonic Motion
Graphing y = A sin (ωx) & y = A cos (ωx) d = a cos(ωt) or d = a sin(ωt)
|A| = amplitude (stretch/shrink vertically)
Damped Harmonic Motion
D'E+ = > F−';E+⁄'2G+ cos I5J −
|A| < 1 shrink |A| > 1 stretch A < 0 reflect
EM
Distance from min to max = 2A 3
KL3
ω = frequency (stretch/shrink horizontally) where a, b, m constants:
|ω| < 1 stretch |ω| > 1 shrink ω < 0 reflect
period = T =
b = damping factor (damping coefficient)
m = mass of oscillating object
|a| = displacement at t = 0
§7.8 Phase Shift =
= period if no damping
y = A sin (ωx – φ) + B
y = A cos (ωx – φ) + B §10.1 Polar Coordinates
Convert Polar to Rectangular Coordinates
§8.1 Inverse Sin, Cos, Tan Fcns x = r cos θ y = r sin θ
y = sin-1 (x) Convert Rectangular to Polar Coordinates
Restrict range to
0,
Restrict range to [-π/2, π/2]
y = cos-1 (x) If x = y = 0 then r = 0, θ can have any value
Restrict range to − ,
else N = CO +
Q X YN Q XZ
y = tan-1 (x)
S tan U
−1 T
Q Q XX YN Q XXX
= tan U + V
−1 T
O = 0, > 0
§8.2 Inverse Trig Fcns (con’t)
y = sec-1 x R ⁄2
O = 0, < 0
where |x| ≥ 1 and 0 ≤ y ≤ π,
Q
y≠
where |x| ≥ 1 and − ≤ y ≤ ,
y = csc-1 x
y≠0 P − ⁄2
y = cot-1 x where -∞ < x < ∞ and 0 < y < π
z = x + yi is ]^ = x + yi
§10.3 Complex Plane & De Moivre’s Theorem
|]| = √] ]^ = CO +
Conjugate of
tan = cot =
§8.3 Trig Identities
Modulus of z:
csc = sec = cot =
# # # Products & Quotients of Complex >bs (Polar)
%& z1 = r1 (cos θ1 + i sin θ1) z2 = r2 (cos θ2 + i sin θ2)
]# ] = N# N
cos'# + + + a sin'# + +
Pythagorean: sin2 θ + cos2 θ = 1
tan2 θ + 1 = sec2 θ cot2 θ + 1 = csc2θ
=
cos'# − + + a sin'# − + z2 ≠ 0-
bc dc
b3 d3
cos'α ± β+ = cos α cos β ∓ sin α sin β
§8.4 Sum & Difference Formulae
sin'α ± β+ = sin α cos β ± cos α sin β ] e = N e
cos 'f+ + a sin'f+
De Moire’s Theorem z = r (cos θ + i sin θ)
tan'α ± β+ = ghijklm nhhop n ≥ 2, k = 0, 1, 2, …, (n – 1))
%& '.+±%& '/+
n≥1
#∓%& '.+ %& '/+
]q = √N rcos e + e + a sin e + e s
q q
sin '2α+ = 2sin α cos α cos '2α+ = cos α − sin α
§8.5 Double-Angle & Half-Angle Formulae
cos '2α+ = 1 − 2 sin α = 2 cos α −1
where k = 0, 1, 2, …, (n – 1)
Dr. Adler SPSU Math 1113 Cheat Sheet: Page 1
>O + ; = A V > ;
§10.4 Vectors §12.3 Systems of Linear Eqns: Determinants
{ D= = (ad – bc) ≠ 0
<O + D = E < D
Unit Vectors
A ; > A
unit vectors: i, j, k in direction x-axis, y-axis, z-axis
Dx = Dy =
E D < E
Add & Subtract Vectors Algebraically
|~
O= =
|}
v = (a1, b1) = a1i + b1j w = (a2, b2) = a2i + b2j
| |
v + w = (a1 + a2)i + (b1 + b2)j = (a1 + a2, b1 + b2) etc.
>## O + ># + ># ] = <#
Cramer’s Rule:
># O + > + > ] = < V
v – w = (a1 – a2)i + (b1 – b2)j = (a1 – a2, b1 – b2)
α v = (α a1)i + (α b1)j = (α a1, α b1)
= 5># + ;# ># O + > + > ] = <
||v|| >## ># >#
D = ># > > ≠ 0
§10.5 The Dot Product ># > >
v = a 1 i + b 1j w = a 2i + b 2j the unique soln of system given by
O= } = ~ ]=
| | |
cos = wtwwvw
t∙v
v · w = a1 a2 + b 1 b 2
Angle between 2 Vectors | | |
vx = wywz y
Properties of Determinates
t∙y
Decompose a Vector into Orthogonal Vectors
Vector projection of v onto w Value of D changes sign if 2 rows interchanged.
vz = v − vx
Value of D changes sign if 2 columns interchanged.
- Draw v & w with same initial pt If all entries in any row are zero, then D = 0
- From terminal pt of v drop ┴ to w If all entries in any column are zero, then D = 0
- This creates rt triangle with v as hypotenuse. If any 2 rows have identical corresponding values then D = 0
- Legs of triangle are decomposition If any 2 columns have identical corresponding values then D = 0
If any row multiplied by (nonzero) number k, D is multiplied by k.
§12.1 Sys of Linear Eqns; Substitution/Elimination If any column multiplied by (nonzero) k, D is multiplied by k.
Solve Systems of Equations by Substitution If entries of any row multiplied by nonzero k and result added to
1. Solve 1 eqn for 1 variable in terms of others. corresponding entries of another row, value of D is unchanged.
2. Substitute result in remaining eqns. If entries of any column multiplied by nonzero k and result added
3. If have eqn in 1 variable, solve it, otherwise loop back to 1 to corresponding entries of another column, D is unchanged.
above.
4. Solve remaining variables, if any, by substituting known values §12.4 Matrix Algebra
<#
in remaining eqns. Product of Row x Column:
<
@ =
N# N … Ne … = N# <# + N < + ⋯ + Ne <e
5. Check soln in original system of eqns.
<e
Solve Systems of Eqns by Elimination
1. Interchange any 2 eqns.
2. Multiply (or divide) each side of eqn by same non-zero Product of rectangular matrices:
constant. A is m x r matrix, B is r x n matrix.
3. Replace any eqn in system by sum (or difference) of that eqn & Aij = Σk Aik Bkj
nonzero multiple of another eqn in system.
Finding Inverse of >onsingular Matrix
§12.2 Systems of Linear Eqns: Matrices To find inverse of n x n nonsingular matrix A:
Row Operations on the Matrix: 1. Form the matrix [A | In].
1. Interchange any 2 rows. 2. Transform [A | In] into reduced row echelon form.
2. Replace a row by nonzero multiple of that row. 3. Reduced row echelon form of [A | In] will contain identity
3. Replace a row by sum of that row and a nonzero multiple of matrix In left of vertical bar; the n x n matrix on right of vertical
some other row. bar is inverse of A.
Matrix Method for Solving System Linear Eqns Solve System Linear Eqns Using Inverse Matrix
1. Write augmented matrix that represents the system. Can write system of eqns as AX = B.
2. Perform row operations that place “1” in locn 1, 1: Perform
If have inverse A-1 then multiply by it.
row operations that place “0” below this.
3. Perform row operations that place “1” in locn 2, 1, leaving X = A-1 B
entries to left unchanged. If this is not possible, move 1 cell to
right and try again. Perform row operations that place “0”
§12.6 Matrix Algebra
below it & to left. Solving by Substitution
4. Repeat step 4, moving one row down and 1 col right. Repeat For system of eqns, pts whose coordinates satisfy all eqns are
until bottom row or vertical bar reached. represented by intersections of the graphs of eqns.
5. Now in row echelon form. Analyze resulting system of eqns for Can also use substitution & or elimination just like systems of
solns to original system of eqns. linear eqns.
Beware of extraneous solns.
Page 2: Cheat Sheet SPSU Math 1113 Dr. Adler
