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Formula Sheet · Class 11 Applied Maths

Class 11 Applied Maths — Formulas at a Glance

Every rule, shortcut and identity for the units we've covered. No worked examples — pure reference for last-minute revision.

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Unit 1 Numbers, Quantification & Numerical Applications

Themes: modular arithmetic, mixture & allegation, motion in streams, work rate, races, partnership profit-sharing, numerical inequalities.

1.1Modulo arithmetic

Modulo (a mod n)
a mod n = remainder when a is divided by n 0 ≤ (a mod n) < n (always non-negative, < n) 17 mod 5 = 2 (17 = 3·5 + 2) 38 mod 7 = 3 (38 = 5·7 + 3)
n is the modulus (a positive integer); a is any integer.
Properties (mod n)
(a + b) mod n = ((a mod n) + (b mod n)) mod n (a − b) mod n = ((a mod n) − (b mod n) + n) mod n (a · b) mod n = ((a mod n) · (b mod n)) mod n
Use these to shrink huge numbers BEFORE multiplying or adding — much faster than computing the full value.
Negative numbers — adjust to non-negative remainder
(−13) mod 5 = (−13 + 5·3) mod 5 ← add 5 until non-negative = 2

1.2Congruence modulo

Congruence — definition
a ≡ b (mod n) ⟺ n divides (a − b) ⟺ a and b have the SAME remainder when divided by n 17 ≡ 2 (mod 5) because 5 | (17 − 2) = 15 24 ≡ 3 (mod 7) because 7 | (24 − 3) = 21
Read as "a is congruent to b modulo n".
Congruence is an equivalence relation
Reflexive: a ≡ a (mod n) Symmetric: a ≡ b ⟹ b ≡ a (mod n) Transitive: a ≡ b and b ≡ c ⟹ a ≡ c (mod n)
Arithmetic on congruences
If a ≡ b (mod n) and c ≡ d (mod n): a + c ≡ b + d (mod n) a − c ≡ b − d (mod n) a · c ≡ b · d (mod n) aᵏ ≡ bᵏ (mod n) for any k ≥ 0
Powers are especially useful — e.g. finding the last digit of 7¹⁰⁰ is (7¹⁰⁰) mod 10.

1.3Allegation & mixture

Rule of allegation
Ratio of cheaper to dearer = (dearer price − mean price) ───────────────────────────── (mean price − cheaper price)
Used when two ingredients of different prices are mixed to get a known mean price; gives the mixing ratio by quantity.
Cross-form (memory aid)
Cheaper (c) Dearer (d) \ / Mean (m) / \ (d − m) (m − c) Ratio of cheaper : dearer = (d − m) : (m − c)
Repeated dilution / replacement
After n equal withdrawals & top-ups with water: pure_left = initial · (1 − x/V)ⁿ x = volume removed and replaced each time V = total volume of the container n = number of withdrawals

1.4Boats & streams

Downstream / upstream speed
Downstream speed = boat speed + stream speed = b + s Upstream speed = boat speed − stream speed = b − s
b = speed of boat in still water; s = speed of the stream/current.
Solving for b and s from downstream / upstream
b = (downstream + upstream) ÷ 2 s = (downstream − upstream) ÷ 2
Time–distance basics (reminder)
distance = speed × time time = distance ÷ speed speed = distance ÷ time

1.5Pipes & cisterns

One-pipe work rate
If a pipe fills a tank in t hours, its rate = 1 / t (tank per hour).
Two pipes filling together
Together, time to fill = (a · b) / (a + b) (where a, b are the individual times — same shortcut as the "two people working together" formula.)
One fills, one drains
Net rate = (1/a) − (1/b) Time = 1 / net rate = (a · b) / (b − a) (a = filling time, b = draining time; assumes b > a.)

1.6Races & games

"A beats B by x metres" — same time, different distance
In the time A finishes the race, B covers (race length − x) metres. ⟹ speed_A : speed_B = L : (L − x) where L = race length.
"A beats B by t seconds" — same distance, different time
Time taken by A : T_A Time taken by B : T_A + t Speed ratio (A : B) = (T_A + t) : T_A
"A gives B a head start of x m" — handicap
A runs L metres while B runs (L − x) metres in the same time. speed_A : speed_B = L : (L − x)

1.7Partnership

Simple partnership (same time period)
Profit-share ratio = ratio of investments If A invests Rs P_A and B invests Rs P_B for the SAME duration, profit(A) : profit(B) = P_A : P_B
Compound partnership (different time periods)
Profit-share ratio = ratio of (investment × time) Equivalent capital = Rs invested × months in business Use these "capital · months" products as the ratio.
Always convert times to the same unit (months or years) before forming the ratio.
Working vs sleeping partner
Working partner: takes a fixed salary OR % of profit FIRST, then the remainder is split in capital ratio. Sleeping partner: invests only — share is purely by capital ratio.

1.8Numerical inequalities

Basic rules for solving inequalities
Add or subtract the same number ─ direction stays the same Multiply / divide by POSITIVE ─ direction stays the same Multiply / divide by NEGATIVE ─ FLIP the direction (< becomes >, ≤ becomes ≥)
The sign-flip on negative multiplication is the most common error — circle every multiplication.
Linear inequality solution — number-line form
Solve 2x − 5 < 7 2x < 12 x < 6 → solution: (−∞, 6)
Double / compound inequality
If a < x < b, apply ANY allowed operation to ALL THREE parts at once. −3 < 2x + 1 ≤ 7 −4 < 2x ≤ 6 (subtract 1 from each part) −2 < x ≤ 3 (divide each part by +2)
A solution like x > 4 means an open interval (the endpoint is not included). x ≥ 4 means a closed endpoint on the left.

Unit 2 Algebra

Themes: binary operations on sets, exponent & logarithm laws, arithmetic & geometric progressions and their sums.

2.1Binary operations

Definition
A binary operation ∗ on a set S is a rule that assigns to every ordered pair (a, b) with a, b ∈ S a UNIQUE element a ∗ b ∈ S.
"Closed under ∗" means a ∗ b stays inside S for every choice of a, b.
Key properties
Commutative: a ∗ b = b ∗ a for all a, b ∈ S Associative: (a ∗ b) ∗ c = a ∗ (b ∗ c) Identity e : a ∗ e = e ∗ a = a (unique if it exists) Inverse a⁻¹: a ∗ a⁻¹ = a⁻¹ ∗ a = e
Quick examples
Addition on ℕ: closed, commutative, associative; identity 0 (not in ℕ⁺); no inverses in ℕ. Multiplication on ℤ: closed, commutative, associative; identity 1; inverses only for ±1. Subtraction on ℤ: closed, NOT commutative, NOT associative.

2.2Indices & laws of exponents

Product, quotient, power
aᵐ · aⁿ = aᵐ⁺ⁿ aᵐ ÷ aⁿ = aᵐ⁻ⁿ (a ≠ 0) (aᵐ)ⁿ = aᵐⁿ (a · b)ⁿ = aⁿ · bⁿ (a / b)ⁿ = aⁿ / bⁿ (b ≠ 0)
Zero, negative & fractional exponents
a⁰ = 1 (a ≠ 0) a⁻ⁿ = 1 / aⁿ (a ≠ 0) a^(1/n) = ⁿ√a a^(m/n) = ⁿ√(aᵐ) = (ⁿ√a)ᵐ
Surd simplification
√(a · b) = √a · √b √(a / b) = √a / √b (b > 0) Rationalise: 1 / (√a + √b) · (√a − √b) / (√a − √b) = (√a − √b) / (a − b)

2.3Logarithm

Definition
log_b x = y ⟺ bʸ = x (b > 0, b ≠ 1, x > 0) log₁₀ 1000 = 3 (because 10³ = 1000) log₂ 32 = 5 (because 2⁵ = 32)
Laws of logarithm
log_b (x · y) = log_b x + log_b y log_b (x / y) = log_b x − log_b y log_b (xⁿ) = n · log_b x log_b 1 = 0 log_b b = 1
Change of base
log_b x = (log_c x) / (log_c b) Common bases: log x = log₁₀ x (common log) ln x = log_e x (natural log, e ≈ 2.71828)
Use change of base to compute any log with a calculator that only has log or ln.

2.4Arithmetic progression (AP)

nth term
aₙ = a + (n − 1) · d a = first term, d = common difference, n = term number.
Sum of first n terms
Sₙ = n/2 · [ 2a + (n − 1) · d ] = n/2 · ( a + aₙ ) (when last term known)
Arithmetic mean
If a, b, c are in AP, then b = (a + c) / 2. Sum of first n natural numbers: 1 + 2 + … + n = n(n+1)/2

2.5Geometric progression (GP)

nth term
aₙ = a · rⁿ⁻¹ a = first term, r = common ratio (r ≠ 0).
Sum of first n terms
Sₙ = a · (rⁿ − 1) / (r − 1) if r > 1 Sₙ = a · (1 − rⁿ) / (1 − r) if r < 1 Sₙ = n · a if r = 1
Sum to infinity & geometric mean
S∞ = a / (1 − r) valid only when |r| < 1 Geometric mean of a and c: b = √(a · c) (a, b, c in GP ⟺ b² = a · c)

Unit 3 Mathematical Reasoning

Themes: statements, logical connectives, truth tables, negation/converse/contrapositive, validity of arguments.

3.1Statements & logical connectives

Statement (proposition)
A STATEMENT is a sentence that is either TRUE or FALSE, but not both. "7 is a prime number." statement (true) "Close the door." NOT a statement (command) "x + 2 = 5" NOT a statement (depends on x)
Basic connectives
Negation ¬p "not p" Conjunction p ∧ q "p and q" Disjunction p ∨ q "p or q" Implication p → q "if p then q" Biconditional p ↔ q "p if and only if q"
Truth tables
p q | p∧q | p∨q | p→q | p↔q T T | T | T | T | T T F | F | T | F | F F T | F | T | T | F F F | F | F | T | T
p → q is false ONLY when p is true and q is false.
Quantifiers
∀x P(x) "for ALL x, P(x) is true" (universal) ∃x P(x) "there EXISTS x such that P(x)" (existential) Negation rule: ¬(∀x P(x)) ≡ ∃x ¬P(x) ¬(∃x P(x)) ≡ ∀x ¬P(x)

3.2Negation, converse, contrapositive

From p → q, four related statements
Original : p → q "if p then q" Converse : q → p "if q then p" Inverse : ¬p → ¬q "if not p then not q" Contrapositive : ¬q → ¬p "if not q then not p"
Only the contrapositive is logically equivalent to the original.
Negation of compound statements (De Morgan)
¬(p ∧ q) ≡ ¬p ∨ ¬q ¬(p ∨ q) ≡ ¬p ∧ ¬q ¬(p → q) ≡ p ∧ ¬q ¬(p ↔ q) ≡ (p ∧ ¬q) ∨ (¬p ∧ q)
Worked example
p → q : "If it rains, the match is cancelled." Converse : If the match is cancelled, it rained. Inverse : If it does not rain, the match is not cancelled. Contrapositive : If the match is not cancelled, it did not rain.

3.3Validity of arguments

Tautology, contradiction, contingency
Tautology : compound statement ALWAYS true e.g. p ∨ ¬p Contradiction : compound statement ALWAYS false e.g. p ∧ ¬p Contingency : sometimes true, sometimes false
Standard inference rules
Modus ponens : p → q, p ⟹ q Modus tollens : p → q, ¬q ⟹ ¬p Hypothetical : p → q, q → r ⟹ p → r Disjunctive : p ∨ q, ¬p ⟹ q
An argument is VALID if, whenever all premises are true, the conclusion is also true.
Proof methods
Direct proof : assume p, deduce q, conclude p → q. Contrapositive proof : assume ¬q, deduce ¬p, conclude p → q. Proof by contradiction: assume ¬(claim), derive a contradiction. Counter-example : ONE case where the claim fails disproves "for all".

Unit 4 Calculus

Themes: functions, limits, differentiation rules and economic applications (marginal cost / revenue, maxima & minima).

4.1Functions

Function — definition
A function f : A → B assigns to each x ∈ A exactly one element f(x) ∈ B. A = domain (allowed inputs) B = codomain range(f) = { f(x) : x ∈ A } ⊆ B
Common function types
Polynomial : f(x) = aₙxⁿ + … + a₁x + a₀ Rational : f(x) = p(x) / q(x) (q(x) ≠ 0) Modulus : f(x) = |x| Exponential : f(x) = aˣ (a > 0, a ≠ 1) Logarithmic : f(x) = log_a x (a > 0, a ≠ 1, x > 0)
Domain quick rules
Denominator ≠ 0 (rule out zeros of q(x)) Even root ≥ 0 (radicand non-negative) log_a x : x > 0

4.2Limits

Limit notation
lim f(x) = L x → a means: f(x) can be made as close to L as we wish by taking x close enough to a (but x ≠ a).
Algebra of limits
lim (f ± g) = lim f ± lim g lim (f · g) = lim f · lim g lim (f / g) = (lim f) / (lim g) (lim g ≠ 0) lim (k · f) = k · lim f
Standard limits
lim (xⁿ − aⁿ) / (x − a) = n · aⁿ⁻¹ x→a lim (eˣ − 1) / x = 1 x→0 lim (log(1 + x)) / x = 1 x→0 lim (1 + 1/x)ˣ = e x→∞

4.3Differentiation

Derivative — first principles
f'(x) = lim ( f(x + h) − f(x) ) / h h→0 Geometrically: slope of the tangent at (x, f(x)).
Standard derivatives
d/dx [ xⁿ ] = n · xⁿ⁻¹ d/dx [ k ] = 0 (constant) d/dx [ eˣ ] = eˣ d/dx [ aˣ ] = aˣ · ln a d/dx [ ln x ] = 1 / x d/dx [ log_a x ] = 1 / (x · ln a)
Rules of differentiation
Sum / difference : (f ± g)' = f' ± g' Constant multiple: (k · f)' = k · f' Product : (f · g)' = f'·g + f·g' Quotient : (f / g)' = (f'·g − f·g') / g² Chain : d/dx [ f(g(x)) ] = f'(g(x)) · g'(x)

4.4Applications (marginal cost / revenue, max-min)

Marginal cost & marginal revenue
MC = dC/dx (rate of change of cost C wrt output x) MR = dR/dx (rate of change of revenue R wrt output x) MP = dP/dx (marginal profit, where P = R − C) Average cost AC = C(x) / x Average revenue AR = R(x) / x
Profit is maximised when MR = MC (and dP/dx = 0).
Increasing / decreasing
f'(x) > 0 on an interval ⟹ f is INCREASING there f'(x) < 0 on an interval ⟹ f is DECREASING there f'(x) = 0 at x = c ⟹ c is a CRITICAL point
Second-derivative test for max / min
At a critical point c (where f'(c) = 0): f''(c) > 0 ⟹ local MINIMUM at c f''(c) < 0 ⟹ local MAXIMUM at c f''(c) = 0 ⟹ test fails — use first-derivative sign change

Unit 5 Probability

Themes: random experiments, sample space, events, probability axioms, conditional & independent events.

5.1Random experiments & sample space

Definitions
Random experiment : an action whose outcome cannot be predicted with certainty in advance. Sample space S : the SET of all possible outcomes. Outcome : a single element of S. Toss a coin : S = { H, T } Roll a die : S = { 1, 2, 3, 4, 5, 6 } Two coins : S = { HH, HT, TH, TT }
Counting outcomes
n(S) = total number of equally likely outcomes n(A) = number of outcomes favourable to event A For two independent stages with m and n outcomes: total outcomes = m · n (multiplication principle)
Types of events
Sure event : A = S (P = 1) Impossible : A = ∅ (P = 0) Simple : A has exactly one outcome Compound : A has more than one outcome Complement A' : all outcomes in S that are NOT in A

5.2Events & probability axioms

Classical (equally likely) probability
P(A) = n(A) / n(S) = favourable outcomes / total outcomes
Requires all outcomes in S to be equally likely.
Axioms of probability
(1) 0 ≤ P(A) ≤ 1 (2) P(S) = 1 (3) If A and B are MUTUALLY EXCLUSIVE (A ∩ B = ∅), P(A ∪ B) = P(A) + P(B)
Addition rule & complement
P(A ∪ B) = P(A) + P(B) − P(A ∩ B) P(A') = 1 − P(A) P(A − B) = P(A) − P(A ∩ B)

5.3Conditional probability

Conditional probability
P(A | B) = P(A ∩ B) / P(B) (P(B) > 0) Read "probability of A GIVEN B". Multiplication rule: P(A ∩ B) = P(B) · P(A | B) = P(A) · P(B | A)
Independent events
A and B are INDEPENDENT ⟺ P(A ∩ B) = P(A) · P(B) Equivalently: P(A | B) = P(A) and P(B | A) = P(B)
Don't confuse independent (no influence) with mutually exclusive (cannot happen together) — these are different ideas.
Law of total probability
If B₁, B₂, …, Bₙ partition the sample space S, P(A) = P(A | B₁)·P(B₁) + P(A | B₂)·P(B₂) + … + P(A | Bₙ)·P(Bₙ)

Unit 6 Descriptive Statistics

Themes: reading data, central tendency, dispersion, skewness, percentiles and quartiles.

6.1Data interpretation

Types of data
Raw (ungrouped) : individual values x₁, x₂, …, xₙ Discrete frequency : value xᵢ with frequency fᵢ Continuous (grouped) : class intervals with class mark xᵢ Total frequency : N = Σ fᵢ Class mark : xᵢ = (lower + upper) / 2 Class width : h = upper − lower
Cumulative frequency (cf)
cfᵢ = f₁ + f₂ + … + fᵢ The cf of a class is the count of all observations up to and including that class. Used in median, quartile and percentile formulas.
Reading bar charts / pie charts
Pie sector angle = (frequency / total) · 360° Pie sector % = (frequency / total) · 100

6.2Central tendency (mean, median, mode)

Mean — three methods
Direct : x̄ = Σ(fᵢ · xᵢ) / N Assumed mean : x̄ = A + Σ(fᵢ · dᵢ) / N dᵢ = xᵢ − A Step-deviation : x̄ = A + h · ( Σ(fᵢ · uᵢ) / N ) uᵢ = (xᵢ − A)/h
A = assumed mean (any convenient class mark); h = class width.
Median (grouped data)
Median = L + h · ( (N/2 − cf) / f ) L = lower limit of the median class N = total frequency cf = cumulative frequency BEFORE the median class f = frequency of the median class h = class width Median class: the class containing the (N/2)ᵗʰ observation.
Mode (grouped data)
Mode = L + h · ( (f₁ − f₀) / (2f₁ − f₀ − f₂) ) L = lower limit of the modal class (highest frequency) f₁ = frequency of the modal class f₀ = frequency of the class BEFORE f₂ = frequency of the class AFTER h = class width Empirical relation: Mode ≈ 3·Median − 2·Mean

6.3Dispersion (range, MD, SD, variance)

Range
Range = Maximum value − Minimum value For grouped data: Range = upper limit of highest class − lower limit of lowest class.
Mean deviation
MD about mean : MD = Σ fᵢ · | xᵢ − x̄ | / N MD about median : MD = Σ fᵢ · | xᵢ − M | / N Coefficient of MD = MD / (mean or median used)
Variance & standard deviation
Variance : σ² = Σ fᵢ · ( xᵢ − x̄ )² / N Std deviation : σ = √ σ² Shortcut : σ² = Σ fᵢ · xᵢ² / N − x̄² Coefficient of variation (CV) = ( σ / x̄ ) · 100 (%) Lower CV ⟹ more consistent data.

6.4Skewness

What skewness measures
Symmetric : Mean = Median = Mode skewness = 0 Positively skewed : Mean > Median > Mode tail on the RIGHT Negatively skewed : Mean < Median < Mode tail on the LEFT
Karl Pearson's coefficient of skewness
Sk = ( Mean − Mode ) / σ = 3 · ( Mean − Median ) / σ (when mode is ill-defined) Range : −3 ≤ Sk ≤ +3 (in practice usually −1 to +1).
Bowley's coefficient (quartile-based)
Sk(Bowley) = ( Q₃ + Q₁ − 2·Q₂ ) / ( Q₃ − Q₁ ) Q₂ = median. Used when extreme values make Karl Pearson unreliable. Range : −1 ≤ Sk(Bowley) ≤ +1.

6.5Percentile & quartile

Quartiles (grouped data)
Qₖ = L + h · ( ( k·N/4 − cf ) / f ) k = 1, 2, 3 Q₁ class: contains (N/4)ᵗʰ observation (lower quartile) Q₂ class: contains (N/2)ᵗʰ observation (= median) Q₃ class: contains (3N/4)ᵗʰ observation (upper quartile)
Percentiles (grouped data)
Pₖ = L + h · ( ( k·N/100 − cf ) / f ) k = 1 … 99 P₂₅ = Q₁, P₅₀ = Q₂ = median, P₇₅ = Q₃.
Inter-quartile range & quartile deviation
IQR = Q₃ − Q₁ QD = ( Q₃ − Q₁ ) / 2 Coefficient of QD = ( Q₃ − Q₁ ) / ( Q₃ + Q₁ )
IQR ignores the extreme 25% on each end — robust against outliers.

Unit 7 Financial Mathematics

Themes: simple & compound interest, nominal vs effective rates, annuities (future value & present value).

7.1Simple interest

Simple interest (SI)
SI = ( P · R · T ) / 100 P = principal (Rs) R = annual rate of interest (%) T = time (years)
Amount under simple interest
A = P + SI = P · ( 1 + R·T / 100 )
Solving for P, R or T
P = 100 · SI / ( R · T ) R = 100 · SI / ( P · T ) T = 100 · SI / ( P · R )

7.2Compound interest

Compound interest — annual compounding
A = P · ( 1 + R/100 ) ᵀ CI = A − P P = principal, R = annual rate (%), T = time (years).
Other compounding frequencies
Half-yearly : A = P · ( 1 + R/200 ) ^(2T) Quarterly : A = P · ( 1 + R/400 ) ^(4T) Monthly : A = P · ( 1 + R/1200 ) ^(12T) General m times a year for T years: A = P · ( 1 + R/(100·m) ) ^(m·T)
CI for fractional time / different rates
If rate changes year-on-year (R₁, R₂, R₃ …): A = P · (1 + R₁/100) · (1 + R₂/100) · (1 + R₃/100) · … Population / depreciation: Growth (rate R%/yr) : A = P · (1 + R/100)ᵀ Depreciation (rate R%/yr) : A = P · (1 − R/100)ᵀ

7.3Nominal vs effective rates

Nominal rate
Nominal rate r : the stated annual rate, ignoring how often compounding actually happens. Per-period rate i = r / m (m = periods per year)
Effective annual rate (EAR)
Effective rate = ( 1 + r/m ) ᵐ − 1 r = nominal annual rate (decimal) m = number of compounding periods per year
EAR is the rate that, compounded ANNUALLY, gives the same yearly growth as r compounded m times.
Quick example
Nominal 12% per annum, compounded quarterly: EAR = ( 1 + 0.12 / 4 )⁴ − 1 = ( 1.03 )⁴ − 1 ≈ 0.1255 ≈ 12.55 % per annum.

7.4Annuities

Annuity — terminology
Annuity : a sequence of EQUAL payments PMT made at EQUAL intervals. Ordinary annuity : payments at the END of each period. Annuity due : payments at the BEGINNING of each period. PMT = periodic payment, i = rate per period, n = number of periods.
Future value (FV) of an ordinary annuity
FV = PMT · ( (1 + i)ⁿ − 1 ) / i Use when saving regularly toward a target (e.g. SIP, recurring deposit). Each payment grows by compound interest until the end of period n.
Present value (PV) of an ordinary annuity
PV = PMT · ( 1 − (1 + i)⁻ⁿ ) / i Use to value a stream of equal future payments today (e.g. loan EMI calculation, pension valuation). Annuity due: multiply the FV or PV formula by (1 + i).

Unit 8 Coordinate Geometry

Themes: distance & section formulas, equations of straight lines, circles, parabolas in standard form.

8.1Straight lines

Distance & section formulas
Distance between P(x₁, y₁) and Q(x₂, y₂): d = √( (x₂ − x₁)² + (y₂ − y₁)² ) Section formula — point dividing PQ in ratio m : n internally : ( (m·x₂ + n·x₁)/(m+n), (m·y₂ + n·y₁)/(m+n) ) midpoint : ( (x₁ + x₂)/2 , (y₁ + y₂)/2 ) Slope m = (y₂ − y₁) / (x₂ − x₁) (x₁ ≠ x₂)
Equation of a line — forms
Slope-intercept : y = m·x + c Point-slope : y − y₁ = m · (x − x₁) Two-point : (y − y₁) / (y₂ − y₁) = (x − x₁) / (x₂ − x₁) Intercept form : x/a + y/b = 1 General form : A·x + B·y + C = 0
For general form: slope = −A/B, x-intercept = −C/A, y-intercept = −C/B.
Parallel, perpendicular, distance
Parallel : m₁ = m₂ Perpendicular : m₁ · m₂ = −1 Distance from point (x₀, y₀) to line A·x + B·y + C = 0: d = | A·x₀ + B·y₀ + C | / √( A² + B² ) Distance between parallel lines A·x + B·y + C₁ = 0 and A·x + B·y + C₂ = 0: d = | C₁ − C₂ | / √( A² + B² )

8.2Circles

Standard form
Centre (h, k), radius r : (x − h)² + (y − k)² = r² Centre at origin : x² + y² = r²
General form
x² + y² + 2·g·x + 2·f·y + c = 0 Centre = ( −g , −f ) Radius = √( g² + f² − c ) Real circle exists only when g² + f² − c > 0.
Position of a point wrt a circle
Let S(x, y) = (x − h)² + (y − k)² − r². S(x₀, y₀) < 0 ⟹ point is INSIDE the circle S(x₀, y₀) = 0 ⟹ point is ON the circle S(x₀, y₀) > 0 ⟹ point is OUTSIDE the circle

8.3Parabola

Standard parabola y² = 4·a·x (opens RIGHT)
Vertex : (0, 0) Focus : (a, 0) Directrix : x = −a Axis : y = 0 (the x-axis) Latus rectum : 4·a (chord through focus ⟂ axis)
Three other standard forms
y² = −4·a·x opens LEFT focus (−a, 0), directrix x = a x² = 4·a·y opens UP focus (0, a), directrix y = −a x² = −4·a·y opens DOWN focus (0, −a), directrix y = a In every case the axis passes through the vertex and the focus, and the latus rectum has length 4·a.
Focal distance & key property
For a point P(x, y) on y² = 4·a·x : focal distance = x + a Defining property of a parabola: distance(P, focus) = distance(P, directrix).
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