Formula Booklet  AIHL

Prior Learning

A=bh
A=21(bh)
A=21(a+b)h
A=πr2
C=2πr
V=lwh
V=πr2h
V=Ah
A=2πrh
d=(x2x1)2+(y2y1)2
(2x1+x2,2y1+y2)
x=2ab±b24ac

Sequences Series

un=u1+(n1)d
Sn=2n(2u1+(n1)d)=2n(u1+un)
un=u1rn−1
Sn=r1u1(rn1)=1ru1(1rn),r=1
S=1ru1,r<1

Financial Mathematics

FV=PV(1+100kr)kn

Exponents & Logs

logab=xax=b, where a>0, b>0, a=1
loga(xy)=logax+logay
logayx=logaxlogay
loga(xm)=mlogax

Approximations Error

ε=vEvAvE×100%

Complex Numbers

z=a+bi
Δ=b24ac
z=r(cosθ+isinθ)=reiθ=rcisθ

Matrices

detA=A=adbc
A−1=detA1(dcba), ad=bc
Mn=PDnP−1

Coordinates & Lines

y=mx+c
ax+by+d=0
yy1=m(xx1)
m=x2x1y2y1

Modelling

x=2ab
f(x)=1+CekxL, L,C,k>0

2&3D Geometry

d=(x2x1)2+(y2y1)2+(z2z1)2
(2x1+x2,2y1+y2,2z1+z2)
V=31Ah
V=31πr2h
A=πrl
V=34πr3
A=4πr2
l=360θ2πr
A=360θπr2
l=rθ
A=21r2θ

Trig IDs

sinAa=sinBb=sinCc
c2=a2+b22abcosC
cosC=2aba2+b2c2
A=21absinC
cos2θ+sin2θ=1
tanθ=cosθsinθ

Matrices

(cos2θsin2θsin2θcos2θ)
(k001)
(100k)
(k00k)
(cosθsinθsinθcosθ)
(cosθsinθsinθcosθ)

Vectors

v=v12+v22+v32
r=a+λb
x=x0+λl,y=y0+λm,z=z0+λn
vw=v1w1+v2w2+v3w3
vw=vwcosθ
cosθ=vwv1w1+v2w2+v3w3
v×w=v2w3v3w2v3w1v1w3v1w2v2w1
v×w=vwsinθ
A=v×w

Descriptive Statistics

IQR=Q3Q1
xˉ=ni=1kfixi
sn2=n1ns2

Probability

P(A)=n(U)n(A)
P(A)+P(A)=1
P(AB)=P(A)+P(B)P(AB)
P(AB)=P(A)+P(B)
P(AB)=P(B)P(AB)
P(AB)=P(A)P(B)
sn=Tns0

Distributions & Vars

E(X)=xP(X=x)
XB(n,p)
E(X)=np
Var(X)=np(1p)
E(aX+b)=aE(X)+b
Var(aX+b)=a2Var(X)
E(a1X1++anXn)=a1E(X1)++anE(Xn)
Var(a1X1++anXn)=a12Var(X1)++an2Var(Xn)
XPo(m)
E(X)=m
Var(X)=m

Differentiation

f(x)=xnf(x)=nxn−1
f(x)=sinxf(x)=cosx
f(x)=cosxf(x)=sinx
f(x)=tanxf(x)=cos2x1
f(x)=exf(x)=ex
f(x)=lnxf(x)=x1
dxdy=dudydxdu
y=uvdxdy=udxdv+vdxdu
y=vudxdy=v2vdxduudxdv

Integration

xndx=n+1xn+1+C,n=−1
A=abydx
abydx2h(y0+2(y1++yn−1)+yn)
x1dx=lnx+C
sinxdx=cosx+C
cosxdx=sinx+C
cos2x1dx=tanx+C
exdx=ex+C
A=abydx or A=abxdy
V=πaby2dx or V=πabx2dy
a=dtdv=dt2d2s
distance =t1t2v(t)∣dt
displacement =t1t2v(t)dt

Differential Equations

yn+1=yn+hf(xn,yn),xn+1=xn+h
xn+1=xn+hf1(xn,yn,tn),yn+1=yn+hf2(xn,yn,tn),tn+1=tn+h
x=Aeλ1tp1+Beλ2tp2

Prior Learning

A=bh
A=21(bh)
A=21(a+b)h
A=πr2
C=2πr
V=lwh
V=πr2h
V=Ah
A=2πrh
d=(x2x1)2+(y2y1)2
(2x1+x2,2y1+y2)
x=2ab±b24ac

Sequences Series

un=u1+(n1)d
Sn=2n(2u1+(n1)d)=2n(u1+un)
un=u1rn−1
Sn=r1u1(rn1)=1ru1(1rn),r=1
S=1ru1,r<1

Financial Mathematics

FV=PV(1+100kr)kn

Exponents & Logs

logab=xax=b, where a>0, b>0, a=1
loga(xy)=logax+logay
logayx=logaxlogay
loga(xm)=mlogax

Approximations Error

ε=vEvAvE×100%

Complex Numbers

z=a+bi
Δ=b24ac
z=r(cosθ+isinθ)=reiθ=rcisθ

Matrices

detA=A=adbc
A−1=detA1(dcba), ad=bc
Mn=PDnP−1

Coordinates & Lines

y=mx+c
ax+by+d=0
yy1=m(xx1)
m=x2x1y2y1

Modelling

x=2ab
f(x)=1+CekxL, L,C,k>0

2&3D Geometry

d=(x2x1)2+(y2y1)2+(z2z1)2
(2x1+x2,2y1+y2,2z1+z2)
V=31Ah
V=31πr2h
A=πrl
V=34πr3
A=4πr2
l=360θ2πr
A=360θπr2
l=rθ
A=21r2θ

Trig IDs

sinAa=sinBb=sinCc
c2=a2+b22abcosC
cosC=2aba2+b2c2
A=21absinC
cos2θ+sin2θ=1
tanθ=cosθsinθ

Matrices

(cos2θsin2θsin2θcos2θ)
(k001)
(100k)
(k00k)
(cosθsinθsinθcosθ)
(cosθsinθsinθcosθ)

Vectors

v=v12+v22+v32
r=a+λb
x=x0+λl,y=y0+λm,z=z0+λn
vw=v1w1+v2w2+v3w3
vw=vwcosθ
cosθ=vwv1w1+v2w2+v3w3
v×w=v2w3v3w2v3w1v1w3v1w2v2w1
v×w=vwsinθ
A=v×w

Descriptive Statistics

IQR=Q3Q1
xˉ=ni=1kfixi
sn2=n1ns2

Probability

P(A)=n(U)n(A)
P(A)+P(A)=1
P(AB)=P(A)+P(B)P(AB)
P(AB)=P(A)+P(B)
P(AB)=P(B)P(AB)
P(AB)=P(A)P(B)
sn=Tns0

Distributions & Vars

E(X)=xP(X=x)
XB(n,p)
E(X)=np
Var(X)=np(1p)
E(aX+b)=aE(X)+b
Var(aX+b)=a2Var(X)
E(a1X1++anXn)=a1E(X1)++anE(Xn)
Var(a1X1++anXn)=a12Var(X1)++an2Var(Xn)
XPo(m)
E(X)=m
Var(X)=m

Differentiation

f(x)=xnf(x)=nxn−1
f(x)=sinxf(x)=cosx
f(x)=cosxf(x)=sinx
f(x)=tanxf(x)=cos2x1
f(x)=exf(x)=ex
f(x)=lnxf(x)=x1
dxdy=dudydxdu
y=uvdxdy=udxdv+vdxdu
y=vudxdy=v2vdxduudxdv

Integration

xndx=n+1xn+1+C,n=−1
A=abydx
abydx2h(y0+2(y1++yn−1)+yn)
x1dx=lnx+C
sinxdx=cosx+C
cosxdx=sinx+C
cos2x1dx=tanx+C
exdx=ex+C
A=abydx or A=abxdy
V=πaby2dx or V=πabx2dy
a=dtdv=dt2d2s
distance =t1t2v(t)∣dt
displacement =t1t2v(t)dt

Differential Equations

yn+1=yn+hf(xn,yn),xn+1=xn+h
xn+1=xn+hf1(xn,yn,tn),yn+1=yn+hf2(xn,yn,tn),tn+1=tn+h
x=Aeλ1tp1+Beλ2tp2