Formulae for A‑level Mathematics AS Mathematics (7356) A‑level Mathematics (7357) v1.2 First issued August 2017 For the new specifications for first teaching from September 2017.
This booklet of formulae is required for all AS and A‑level Mathematics exams. There is a larger booklet of formulae and statistical tables for all AS and A‑level Further Mathematics exams.
Page Bros/E7
MFB8
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Contents
Page
Pure mathematics
4
Mechanics
6
Probability and statistics
6
4
Pure mathematics Binomial series n n n (a + b) n = a n + a n −1b + a n − 2b2 + … + a n − r b r + … + b n 1 2 r
(n ∈ )
n n! where = n Cr = r!(n − r )! r (1 + x) n = 1 + nx +
n(n − 1) 2 n(n − 1) … (n − r + 1) r x +…+ x + … ( x < 1, n ∈ ) 1.2 1.2… r
Arithmetic series 1 2
1 2
Sn = n (a + l) = n [2a + (n − 1)d] Geometric series Sn =
a (1 − r n ) 1− r
S∞ =
a for | r | < 1 1− r
Trigonometry: small angles For small angle θ, measured in radians: sin θ ≈ θ cos θ ≈ 1 −
θ2 2
tan θ ≈ θ Trigonometric identities sin (A ± B) = sin A cos B ± cos A sin B cos (A ± B) = cos A cos B sin A sin B tan (A ± B) =
tan A ± tan B 1 (A ± B ≠ (k + )π) 2 1 tan A tan B
5
Differentiation f(x)
f ′(x)
tan x sec2 x cosec x
−cosec x cot x
sec x sec x tan x cot x
−cosec2 x
f ( x) g( x)
f ( x) g( x) − f ( x) g( x) (g( x))2
Differentiation from first principles f ( x + h) − f ( x ) h→0 h
f ( x) = lim
Integration
∫
u
dv du dx = uv − v dx dx dx
∫
f ( x) d x = ln | f ( x) | + c f ( x)
∫
f(x)
∫ f(x) dx
tan x
ln | sec x | + c
cot x
ln | sin x | + c
Numerical solution of equations The Newton-Raphson iteration for solving f (x) = 0: xn+1 = xn −
f ( xn ) f ( xn )
Numerical integration The trapezium rule:
b
∫a y dx ≈
1 h{(y0 + yn) + 2(y1 + y2 + … + yn−1)}, 2
where h =
b−a n
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Mechanics Constant acceleration s = ut + 1 at 2
s = ut + 1 at 2
s = vt − 1 at 2
s = vt − 1 at 2
v = u + at
v = u + at
s = 1 (u + v)t
s = 1 (u + v)t
2
2
2
2
2
2
v 2 = u2 + 2as
Probability and statistics Probability P(A ∪ B) = P(A) + P(B) − P(A ∩ B) P(A ∩ B) = P(A) × P(B | A) Standard deviation Σ( x − x)2 = n
Σ x2 − x2 n
Discrete distributions Distribution of X Binomial B(n, p)
P(X = x)
Mean
Variance
n x n − x x p (1 − p)
np
np(1 − p)
Sampling distributions For a random sample of n observations from N( μ, σ 2):
X −μ ~ N(0, 1) σ n End of formulae
(MFB8)