Predicting What Comes Next - Exploring Sequences and Progressions

Look at 1,3,6,10,15,…1, 3, 6, 10, 15, \ldots and something clicks: each number is a stack of dots forming a triangle, and each term is the sum of the counting numbers up to that point. Look at 1,4,9,16,25,…1, 4, 9, 16, 25, \ldots and a different pattern clicks: each is a perfect square, and each is built by adding the next odd number to the one before it. Patterns like these sit inside a taxi fare that climbs by a fixed amount every kilometre, inside a courtyard of tiles that grows by the same number of squares at every stage, inside a bouncing ball whose peak height shrinks by the same fraction on every bounce, and inside a fractal that keeps tripling its pieces while its area keeps shrinking. This chapter gives these ordered lists a name — sequence — and builds two precise, complementary tools for describing, extending and predicting them: an explicit rule that jumps straight to any term from its position, and a recursive rule that builds each term from the one before. Two families of sequences turn out to be so common that they get their own names and formulas. An arithmetic progression (AP) grows by adding the same fixed number at every step, so its terms, when plotted, line up on a straight line. A geometric progression (GP) grows by multiplying by the same fixed number at every step, so its terms curve away from any straight line — slowly at first, then explosively — which is why fractals, compound growth and bouncing balls all hide GPs inside them. Along the way this chapter proves one of mathematics' oldest results, the sum of the first nn natural numbers, using a trick told of a young Gauss and recorded a thousand years earlier by Āryabhaṭa. By the end, a jumble of numbers like 200,240,280,320,…200, 240, 280, 320, \ldots or 3,6,12,24,…3, 6, 12, 24, \ldots will not look mysterious — you will recognise the kind of progression instantly, write down its rule, and predict any term, the hundredth or the thousandth, without writing out everything before it.

Key takeaways
  • A sequence is an ordered list of numbers called terms, written t1,t2,t3,…t_1, t_2, t_3, \ldots using position subscripts; sequences may be finite or infinite.
  • An explicit rule gives tnt_n directly as a formula in nn, for example tn=2n−1t_n=2n-1 for odd numbers — no earlier term is needed.
  • A recursive rule builds each term from the one (or more) before it, for example t1=1, tn=tn−1+3t_1=1,\ t_n=t_{n-1}+3 for n≥2n\geq2 — earlier terms must be known first.
  • The Virahānka-Fibonacci sequence, 1,1,2,3,5,8,13,…1, 1, 2, 3, 5, 8, 13, \ldots, uses two previous terms at once, Vn=Vn−1+Vn−2V_n=V_{n-1}+V_{n-2}; discovered by Virahānka in the 7th century CE studying Prakrit poetic meters.
  • An arithmetic progression (AP) has a constant common difference dd; its rule is tn=a+(n−1)dt_n=a+(n-1)d, and its points (n,tn)(n,t_n) always lie on a straight line.
  • A geometric progression (GP) has a constant common ratio rr; its rule is tn=a⋅r n−1t_n=a\cdot r^{\,n-1}, and its points never lie on a straight line — they curve.
  • The sum of the first nn natural numbers is Sn=n(n+1)2S_n=\dfrac{n(n+1)}{2}, proved by pairing each term with its mirror image in the reversed sum; also the explicit rule for the triangular numbers.
  • Many real growth patterns hide a progression: taxi fares and stage-wise tile patterns are APs; bouncing-ball heights and the Sierpiński triangle's black-triangle count are GPs.
  • Key idea: every sequence is either described by an explicit rule (position tells you the value directly) or a recursive rule (each term is built from earlier ones), and the two most important recursive families — arithmetic progressions, which add a constant difference, and geometric progressions, which multiply by a constant ratio — have explicit formulas tn = a + (n-1)d and tn = a·r^(n-1) that turn "predict any term" into one substitution.
The core insight

A sequence is an ordered list of terms t1,t2,t3,…t_1, t_2, t_3, \ldots described either by an explicit rule (a formula for tnt_n in terms of the position nn) or a recursive rule (each term built from earlier terms), and the two central named patterns — the arithmetic progression, which adds a constant common difference dd so tn=a+(n−1)dt_n = a+(n-1)d and plots as a straight line, and the geometric progression, which multiplies by a constant common ratio rr so tn=a⋅r n−1t_n = a\cdot r^{\,n-1} and plots as a curve — together with the classical sum Sn=n(n+1)/2S_n = n(n+1)/2 for the first nn natural numbers, let you predict, check and add up terms without ever listing them all.

What this chapter covers

The chapter builds a small, sturdy toolkit in a fixed order — first the general idea of a sequence, then two ways of writing a rule for one, and finally the two most important special sequences.

  • Section 8.1 defines a sequence as an ordered list of terms, introduces subscript notation t1,t2,t3,…t_1, t_2, t_3, \ldots, and separates finite from infinite sequences using natural numbers, odd numbers, triangular numbers and square numbers.
  • Section 8.2 introduces the explicit rule, a formula for tnt_n directly in nn, letting you jump to any term or check whether a given number belongs to the sequence, and at what position.
  • Section 8.3 introduces the recursive rule, building each term from the one before (or, for the Virahānka-Fibonacci sequence, the two before), contrasted with the explicit rule.
  • Section 8.4 defines the arithmetic progression (AP) — constant common difference — derives tn=a+(n−1)dt_n=a+(n-1)d from a growing tile pattern, and shows its terms plot as a straight line.
  • Section 8.5 proves the classical sum of the first nn natural numbers, Sn=n(n+1)/2S_n=n(n+1)/2, via the reverse-and-add trick, connected to the triangular numbers of Section 8.1.
  • Section 8.6 defines the geometric progression (GP) — constant common ratio — derives tn=a⋅r n−1t_n=a\cdot r^{\,n-1}, contrasts its curved plot with an AP's line, and applies it to the Sierpiński triangle and a bouncing ball.

Worked examples below reuse NCERT's own example numbers wherever the source text names them directly, so you can cross-check against your textbook.

The core ideas

Sequences, terms and the subscript notation

A sequence is an ordered list of numbers in which each number is called a term. Order matters — 1,3,5,71, 3, 5, 7 is not the same sequence as 7,5,3,17, 5, 3, 1. A sequence may be finite, like 6,12,24,48,966, 12, 24, 48, 96, or infinite, like the natural numbers 1,2,3,4,…1, 2, 3, 4, \ldots, where the dots signal the pattern continues forever. To talk about a general term without knowing its value, mathematicians use subscript notation: t1t_1 is the first term, t2t_2 the second, and tnt_n the term in the nnth position.

t1, t2, t3, …, tn, …t_1,\ t_2,\ t_3,\ \ldots,\ t_n,\ \ldots

where: the subscript matches the position of the term, never its value — t4=7t_4 = 7 means "the fourth term equals 77," not a fourth power. Different sequences discussed together get different letters, tnt_n for one and sns_n or unu_n for another. The position nn is always a natural number, but the term tnt_n itself can be any real number — an integer, fraction, or negative, as in −7,−3,1,5,9,…-7, -3, 1, 5, 9, \ldots where s1=−7s_1=-7.

Explicit rule for the nth term

An explicit rule gives tnt_n directly as an expression in nn, so any term can be found by substituting its position — no earlier terms are needed. For the odd numbers, the rule is un=2n−1u_n = 2n-1, and substituting n=1,2,3,…n=1,2,3,\ldots gives u1=1u_1=1, u2=3u_2=3, u3=5u_3=5, matching 1,3,5,7,9,…1,3,5,7,9,\ldots.

un=2n−1.u_n = 2n - 1.

where: nn is the position and unu_n is its value. The power of an explicit rule shows for large positions: the 300300th term needs one substitution, u300=2(300)−1=599u_{300}=2(300)-1=599, with no earlier terms written out. It also answers the reverse question — is a given number a term, and which one? To check 137137, solve 2n−1=1372n-1=137, giving n=69n=69; since 6969 is a natural number, 137137 is the 6969th term. If solving for nn gives a fraction or a negative number, the number is not a term of that sequence at all.

Recursive rule for the nth term

A recursive rule gives a term in relation to the term (or terms) immediately before it, rather than its position alone. In 1,4,7,10,13,…1, 4, 7, 10, 13, \ldots, every term is 33 more than the one before, so t2=t1+3t_2=t_1+3, t3=t2+3t_3=t_2+3, and in general tn=tn−1+3t_n=t_{n-1}+3 for n≥2n\geq2, together with the starting value t1=1t_1=1.

t1=a,tn=tn−1+dfor n≥2.t_1 = a, \qquad t_n = t_{n-1} + d \quad \text{for } n \geq 2.

where: aa is the first term and dd is the fixed number added each step; unlike an explicit rule, this needs every earlier term — there is no shortcut to the 300300th term without first computing the 299299 before it. This describes the same sequence a different way: for 1,4,7,10,…1,4,7,10,\ldots, both tn=3n−2t_n=3n-2 (explicit) and t1=1, tn=tn−1+3t_1=1,\ t_n=t_{n-1}+3 (recursive) generate the identical list, worth checking against each other for a few values of nn.

The Virahānka-Fibonacci sequence

A recursive rule need not use only the single previous term — it can reach back two terms or more. The most celebrated example is V1=1, V2=2V_1=1,\ V_2=2, and Vn=Vn−1+Vn−2V_n=V_{n-1}+V_{n-2} for n≥3n\geq3, giving 1,2,3,5,8,13,21,34,…1, 2, 3, 5, 8, 13, 21, 34, \ldots, where every term after the second is the sum of the two before it.

V1=1,V2=2,Vn=Vn−1+Vn−2  (n≥3).V_1 = 1,\quad V_2 = 2,\quad V_n = V_{n-1} + V_{n-2} \ \ (n \geq 3).

where: each new term needs both predecessors, not just one, so V5V_5 requires knowing V4=5V_4=5 and V3=3V_3=3, giving V5=5+3=8V_5=5+3=8. This sequence was first written down by the Indian scholar Virahānka in his 7th-century work on Prakrit poetic meter, studied further by Gopāla and Hemachandra, and later popularised in Europe by Fibonacci around 1200 CE — hence its double name. It reappears throughout mathematics and nature as the standard example of a recursion using more than one earlier term.

Arithmetic progressions and their nth term

Consider a growing tile pattern where every stage adds four squares to the corners of the last: 1,5,9,13,17,…1, 5, 9, 13, 17, \ldots. Rewriting each term as the first term plus a whole number of jumps, 1,1+1×4,1+2×4,1+3×4,…1, 1+1\times4, 1+2\times4, 1+3\times4, \ldots, reveals tn=1+(n−1)×4t_n=1+(n-1)\times4. Any sequence built this way — adding the same fixed number at every step — is an arithmetic progression, or AP.

a, a+d, a+2d, a+3d, …, a+(n−1)d, …⇒tn=a+(n−1)d.a,\ a+d,\ a+2d,\ a+3d,\ \ldots,\ a+(n-1)d,\ \ldots \qquad\Rightarrow\qquad t_n = a+(n-1)d.

where: aa is the first term and dd is the common difference, the constant amount added each step (found as t2−t1t_2-t_1, or any tk+1−tkt_{k+1}-t_k). It can be negative — in 11,7,3,−1,−5,…11, 7, 3, -1, -5, \ldots, a=11a=11 and d=−4d=-4, since the terms decrease. Not every "patterned" sequence is an AP: primes 2,3,5,7,11,…2, 3, 5, 7, 11, \ldots have no constant difference at all, so they form a sequence but not a progression. The recursive rule for an AP is simply t1=a, tn=tn−1+dt_1=a,\ t_n=t_{n-1}+d for n≥2n\geq2.

Visualising an AP: points on a straight line

Plot each term of an AP against its position, the ordered pairs (n,tn)(n, t_n), and a striking fact appears: every point lies on one straight line. For 1,5,9,13,171, 5, 9, 13, 17, the pairs (1,1),(2,5),(3,9),(4,13),(5,17)(1,1), (2,5), (3,9), (4,13), (5,17) line up exactly, because tn=4n−3t_n=4n-3 is a linear function of nn, and the graph of a linear function is always a straight line.

Figure
A graph of the arithmetic progression one five nine thirteen seventeen with the five points plotted against their position number and lying exactly on a single straight line
An AP always plots as points on a straight line stage number n number of squares tn 1 2 3 4 5 1 5 9 13 17 (1, 1) (2, 5) (3, 9) (4, 13) (5, 17) tn = 4n minus 3, a straight line of slope 4, the common difference

where: the slope of the line is exactly the common difference dd, since moving one step along nn always moves dd units along tnt_n — a fast diagnostic: if plotted points do not lie on a straight line, the sequence is not an AP, however regular it looks.

Sum of the first n natural numbers

Before the full derivation below, the idea is worth stating on its own: the sum of the first nn natural numbers has a closed form avoiding adding them one by one.

Sn=1+2+3+⋯+n=n(n+1)2.S_n = 1+2+3+\cdots+n = \frac{n(n+1)}{2}.

where: SnS_n is the sum of the first nn natural numbers. This is also the explicit rule for the triangular numbers 1,3,6,10,15,…1, 3, 6, 10, 15, \ldots from Section 8.1, since the nnth triangular number is exactly this sum. The formula turns a sum of a hundred or a million terms into one multiplication and one division.

Figure
A dot diagram showing the sum one plus two plus three plus four plus five plus six doubled and rearranged into a rectangular array of seven columns and six rows to prove the sum equals twenty-one
Doubling the triangle of dots gives a 7 by 6 rectangle 2 times (1+2+3+4+5+6) = 7 times 6 = 42, so the sum 1+2+3+4+5+6 = 21 blue dots are the original triangle, gold dots are the reversed copy that completes the rectangle

Geometric progressions and their nth term

Now consider a growing pattern where the count of green squares doubles every stage: 3,6,12,24,…3, 6, 12, 24, \ldots. Rewriting each term as the first term times a whole number of doublings, 3, 3×2, 3×22, 3×23, …3,\ 3\times2,\ 3\times2^2,\ 3\times2^3,\ \ldots, reveals tn=3×2 n−1t_n=3\times2^{\,n-1}. Any sequence built this way — multiplying by the same fixed number every step — is a geometric progression, or GP.

a, ar, ar2, ar3, …, ar n−1, …⇒tn=a r n−1.a,\ ar,\ ar^2,\ ar^3,\ \ldots,\ ar^{\,n-1},\ \ldots \qquad\Rightarrow\qquad t_n = a\, r^{\,n-1}.

where: aa is the first term and rr is the common ratio, found by dividing any term by the one before it, r=tk+1/tkr=t_{k+1}/t_k, and it must be the same for every consecutive pair — checking two or three ratios, not one, confirms a genuine GP. The ratio can be a fraction less than 11, so terms shrink, as in a bouncing ball's heights; it can also be negative, as in 1,−1,1,−1,…1, -1, 1, -1, \ldots with r=−1r=-1. The recursive rule is t1=a, tn=r⋅tn−1t_1=a,\ t_n=r\cdot t_{n-1} for n≥2n\geq2 — multiplying, not adding, the essential contrast with an AP.

Visualising a GP and the Sierpiński fractals

Plot a GP's terms against position and the points curve away from any straight line — slowly if rr is close to 11, dramatically otherwise. For 3,6,12,24,48,…3, 6, 12, 24, 48, \ldots, the pairs (1,3),(2,6),(3,12),(4,24),(5,48)(1,3), (2,6), (3,12), (4,24), (5,48) rise faster and faster, since tn=3×2 n−1t_n=3\times2^{\,n-1} is exponential in nn, not linear.

Figure
A graph of the geometric progression three six twelve twenty four forty eight with the five points plotted against their position number curving sharply upward and never lying on a straight line
A GP never plots as points on a straight line stage number n number of squares tn 1 2 3 4 5 3 6 12 24 48 (1, 3) (2, 6) (3, 12) (4, 24) (5, 48) tn = 3 times 2 to the power n minus 1, curving because it is exponential in n

where: the curve bends upward more sharply as nn grows because each step multiplies, so the gaps between terms keep growing, unlike an AP where every gap is the fixed dd. The same exponential behaviour explains the Sierpiński triangle, a fractal built by repeatedly removing the central triangle from every black triangle remaining: black triangles at stage nn number tn=3 nt_n=3^{\,n} (a GP, a=1,r=3a=1, r=3), while the area of the black region shrinks as a GP with a=1,r=34a=1, r=\tfrac{3}{4} — triangles multiply explosively even as their total area shrinks toward zero.

Deriving the key results

Derivation AThe sum of the first n natural numbers

The goal of this derivation is to find and prove, for any whole number nn, a closed formula for Sn=1+2+3+⋯+nS_n = 1+2+3+\cdots+n that avoids adding the terms one at a time, starting only from the observation that writing the same sum forwards and backwards and adding the two copies makes every pairing equal. The strategy generalises a trick usually told about the young Gauss and recorded formally in Āryabhaṭa's Āryabhaṭīya (Chapter 2, Verse 19): pair the first term with the last, the second with the second-last, and notice every pair adds to the same total.

Step 1. Write the sum of the first ten natural numbers twice, once forwards and once backwards: S=1+2+3+4+5+6+7+8+9+10S = 1+2+3+4+5+6+7+8+9+10 and also S=10+9+8+7+6+5+4+3+2+1S = 10+9+8+7+6+5+4+3+2+1, since reversing a sum never changes its value.

Step 2. Add the two lines term by term, matching positions. Every matched pair sums to the same constant: 1+10=111+10=11, 2+9=112+9=11, 3+8=113+8=11, down to 10+1=1110+1=11 — ten pairs, each 1111, because as one number in a pair grows by one, its partner shrinks by exactly one.

Step 3. Read off 2S2S: adding the two lines gives 2S=11+11+⋯+112S = 11+11+\cdots+11, that is 1111 added ten times, so 2S=1102S=110 and S=55S=55 — confirmed without adding ten numbers one by one.

Step 4. Generalise from ten terms to any nn terms. Let S=1+2+⋯+nS = 1+2+\cdots+n, and write it in reverse, S=n+(n−1)+⋯+1S = n+(n-1)+\cdots+1. Every one of the nn pairs now sums to the constant (n+1)(n+1), since a pair is always kk and (n+1−k)(n+1-k) for some kk, and k+(n+1−k)=n+1k+(n+1-k)=n+1 regardless of kk.

Step 5. Collect the result: 2S=n×(n+1)2S = n\times(n+1), since there are nn pairs, each (n+1)(n+1). Dividing by 22 gives the general formula, valid for every natural number nn: Sn=n(n+1)2S_n = \dfrac{n(n+1)}{2}. A dot picture makes the same argument visual: two copies of a triangular arrangement of 1+2+⋯+n1+2+\cdots+n dots interlock into a rectangle of nn rows and (n+1)(n+1) columns, area n(n+1)n(n+1) — twice the triangle, exactly as the algebra says. Verified: S10=10×112=55S_{10} = \tfrac{10\times11}{2} = 55; S6=6×72=21S_6 = \tfrac{6\times7}{2}=21, matching the seven-by-six rectangle of 4242 dots split into two triangles of 2121.

Go deeper · Derivation B · 1 minThe explicit nth-term formulas for an AP and a GP, unrolled from their recursive rules
Derivation BThe explicit nth-term formulas for an AP and a GP, unrolled from their recursive rules

The goal of this derivation is to start from nothing but the recursive definitions of an arithmetic progression and a geometric progression — each term built from the one just before it — and to unroll that recursion, step after step, until a direct formula for the nnth term in terms of nn alone falls out, with no reference to any earlier term. The method is the same for both progressions: write out several terms by hand, spot the pattern in how many copies of dd (or factors of rr) have accumulated, and state that pattern for a general position nn.

Step 1. Start from the AP's recursive rule, t1=at_1=a and tn=tn−1+dt_n=t_{n-1}+d for n≥2n\geq2, and unroll it: t2=t1+d=a+dt_2=t_1+d=a+d; then t3=t2+d=(a+d)+d=a+2dt_3=t_2+d=(a+d)+d=a+2d; then t4=t3+d=(a+2d)+d=a+3dt_4=t_3+d=(a+2d)+d=a+3d.

Step 2. Read the pattern: reaching t2t_2 added one copy of dd, t3t_3 two copies, t4t_4 three copies. In general, reaching tnt_n from t1t_1 takes exactly (n−1)(n-1) jumps, each adding one dd. This gives tn=a+(n−1)dt_n=a+(n-1)d, matching the general AP rule.

Step 3. Now start from the GP's recursive rule, t1=at_1=a and tn=r⋅tn−1t_n=r\cdot t_{n-1} for n≥2n\geq2, and unroll it the same way: t2=r⋅t1=art_2=r\cdot t_1=ar; then t3=r⋅t2=r(ar)=ar2t_3=r\cdot t_2=r(ar)=ar^2; then t4=r⋅t3=r(ar2)=ar3t_4=r\cdot t_3=r(ar^2)=ar^3.

Step 4. Read the pattern: reaching t2t_2 used one factor of rr, t3t_3 two factors, t4t_4 three factors — again (n−1)(n-1) factors to reach tnt_n from t1t_1. This gives tn=a r n−1t_n=a\,r^{\,n-1}, matching the general GP rule, multiplication replacing addition at every jump.

Step 5. Verify with a numerical check. For the AP 1,5,9,13,17,…1,5,9,13,17,\ldots (a=1,d=4a=1,d=4), Step 2 predicts t5=1+4(4)=17t_5=1+4(4)=17, matching directly. For the GP 3,6,12,24,48,…3,6,12,24,48,\ldots (a=3,r=2a=3,r=2), Step 4 predicts t5=3(24)=48t_5=3(2^4)=48, again matching directly — confirming that unrolling the same number of steps, but multiplying instead of adding, is what turns a recursive rule into an explicit one. Verified: AP with a=1,d=4a=1,d=4 gives t5=17t_5=17; GP with a=3,r=2a=3,r=2 gives t5=48t_5=48; both match the terms generated directly from the recursive rules.

Worked examples

Board level - Checking membership using an explicit rule

Consider the sequence generated by the explicit formula sn=5n−2s_n = 5n-2. Write its first six terms, find its 100100th term, and check whether 308308 and 471471 are terms of this sequence (this reuses NCERT's own Example 2).

Step 1. Substitute n=1,2,…,6n=1,2,\ldots,6 into sn=5n−2s_n=5n-2: the first six terms are 3,8,13,18,23,283, 8, 13, 18, 23, 28.

Step 2. Substitute n=100n=100 directly, with no need for earlier terms: s100=5(100)−2=498s_{100}=5(100)-2=498.

Step 3. To check 308308, solve 5n−2=3085n-2=308: this gives 5n=3105n=310, so n=62n=62, a natural number, confirming 308308 is the 6262nd term.

Step 4. To check 471471, solve 5n−2=4715n-2=471: this gives 5n=4735n=473, so n=94.6n=94.6, not a natural number, so 471471 is not a term. First six terms: 3,8,13,18,23,283, 8, 13, 18, 23, 28; s100=498s_{100}=\mathbf{498}; 308308 is the 62\mathbf{62}nd term; 471471 is not a term.

Board level - Generating and checking terms with a recursive rule

Find the first four terms of the sequence given by the recursive rule u1=1, un=2un−1+3u_1=1,\ u_n = 2u_{n-1}+3 for n≥2n \geq 2. Is 133133 a term of this sequence (this reuses NCERT's own Example 3)?

Step 1. Compute term by term, since a recursive rule needs the previous value: u2=2u1+3=2(1)+3=5u_2=2u_1+3=2(1)+3=5.

Step 2. Continue: u3=2u2+3=2(5)+3=13u_3=2u_2+3=2(5)+3=13, then u4=2u3+3=2(13)+3=29u_4=2u_3+3=2(13)+3=29. So the first four terms are 1,5,13,291, 5, 13, 29.

Step 3. To check 133133, keep computing forward, since there is no explicit shortcut here: u5=2(29)+3=61u_5=2(29)+3=61, u6=2(61)+3=125u_6=2(61)+3=125, u7=2(125)+3=253u_7=2(125)+3=253.

Step 4. The sequence jumps from u6=125u_6=125 straight to u7=253u_7=253, stepping over 133133 entirely, and every later term only grows larger. The first four terms are 1,5,13,291, 5, 13, 29, and 133133 is not\mathbf{not} a term of this sequence.

Higher-order thinking (HOTS / olympiad-style) - An AP from two given terms

An AP consists of 5050 terms in which the 33rd term is 1212 and the last (5050th) term is 106106. Find the 2929th term (this reuses NCERT's own Exercise Set 8.2, Question 4).

Step 1. Translate both given facts into the AP formula tn=a+(n−1)dt_n = a+(n-1)d. The 33rd term gives a+2d=12a+2d=12, and the 5050th (last) term gives a+49d=106a+49d=106 — two linear equations in the two unknowns aa and dd.

Step 2. Subtract the first equation from the second to eliminate aa: (a+49d)−(a+2d)=106−12(a+49d)-(a+2d) = 106-12, giving 47d=9447d = 94, so d=2d=2.

Step 3. Substitute d=2d=2 back into a+2d=12a+2d=12: a+4=12a+4=12, so a=8a=8. The AP is 8,10,12,14,…8, 10, 12, 14, \ldots, and it is worth checking: the 5050th term should be a+49d=8+98=106a+49d = 8+98=106, which matches.

Step 4. Find the 2929th term using the same formula: t29=a+28d=8+28(2)=8+56=64t_{29} = a+28d = 8+28(2) = 8+56 = 64. The 2929th term is 64\mathbf{64}. Timing note: about three minutes. The whole problem is two simultaneous linear equations disguised inside AP language — the moment you see two terms given by position, translate both into a+(n−1)da+(n-1)d immediately rather than trying to guess aa and dd by inspection. Always sanity-check by re-substituting into both original conditions (the 33rd and 5050th terms), not just one, since a value of dd that satisfies only one equation is worthless.

Common traps

  • Treating any "patterned" list as an AP or a GP. Primes 2,3,5,7,11,…2, 3, 5, 7, 11, \ldots have no constant difference or ratio; always compute two or three consecutive differences (or ratios) before naming a sequence an AP or a GP.
  • Forgetting the (n−1)(n-1), not nn, in both nth-term formulas. Both tn=a+(n−1)dt_n=a+(n-1)d and tn=a r n−1t_n=a\,r^{\,n-1} use (n−1)(n-1) jumps to reach position nn from position 11; writing a+nda+nd or a rna\,r^n shifts every term by one position.
  • Accepting a fractional or negative position as an answer. If solving tn=t_n= (given number) for nn gives anything but a natural number, that number is simply not a term of the sequence.
  • Confusing addition and multiplication between AP and GP. An AP's recursive rule adds dd; a GP's multiplies by rr. Mixing the two up is the commonest slip when a problem states both kinds together.
  • Checking only one pair of terms for a common ratio. A GP's ratio must match for every consecutive pair; one matching pair followed by a mismatch means it is not a GP.
  • Mixing up stage numbering with term numbering in fractal problems. The Sierpiński triangle often starts at Stage 00, so tn=3nt_n=3^n uses the stage number directly — check whether numbering starts at 00 or 11 before applying a formula.

You should be able to…

  • Define a sequence and a term, and distinguish a finite sequence from an infinite one.
  • Read and write subscript notation such as tnt_n, sns_n, unu_n, matching the subscript to the term's position.
  • Use an explicit rule to find any term directly, and check whether a given number is a term (and at which position).
  • Use a recursive rule, including one depending on two previous terms like the Virahānka-Fibonacci sequence, to build up terms from a starting value.
  • Identify an AP, find its first term aa and common difference dd, and write its explicit and recursive rules.
  • Recognise an AP visually: its terms, plotted against position, always lie on a straight line.
  • Derive and apply Sn=n(n+1)2S_n = \dfrac{n(n+1)}{2} for the sum of the first nn natural numbers, and connect it to the triangular numbers.
  • Identify a GP, find its first term aa and common ratio rr, and write its explicit and recursive rules.
  • Recognise a GP visually: its terms curve away from a straight line, as in fractals and bouncing-ball heights.
  • Decide, given an unfamiliar sequence, whether it is an AP, a GP, or neither, by testing for a constant difference or ratio.

Ask the tutor: Want to practice spotting whether a mixed batch of sequences are APs, GPs, or neither, or work through a few more "which term is this number" problems until the natural-number check becomes automatic?

What is actually the difference between a sequence and a progression?

Every progression is a sequence, but not every sequence is a progression. A sequence is any ordered list of numbers, whether or not it follows a neat rule — the primes 2,3,5,7,11,…2,3,5,7,11,\ldots are a perfectly good sequence with no known simple formula. A progression is a special, well-behaved sequence: an AP adds the same fixed number at every step, a GP multiplies by the same fixed number at every step. So when a problem says "AP" or "GP," it is promising constant structure exists, which is what lets you write a clean explicit formula; a plain "sequence" makes no such promise.

How do I know whether to use the explicit rule or the recursive rule when solving a problem?

Look at what the problem hands you and what it asks for. If given a formula in nn directly, or asked for a distant term like the 100100th, use the explicit rule and substitute — it is almost always faster. If told how each term relates to the one (or two) before it, and asked to build up several terms from a known start, use the recursive rule and compute forward. Some sequences, like the Virahānka-Fibonacci sequence, are given only recursively because no simple explicit formula is taught at this level, so there is no choice at all.

Why can't the position n ever come out as a decimal or a negative number when I solve for a term's position?

Because nn is not just any number — it labels a physical position in an ordered list: first, second, third, and so on. There is no "94.694.6th" term of a sequence, in the same way there is no 94.694.6th person standing in a queue. So whenever an equation like 5n−2=4715n-2=471 gives n=94.6n=94.6, that is not an answer to round or accept — it is proof that 471471 never appears in that sequence at all. Always finish a "is this number a term" question by checking your value of nn is a positive whole number before declaring it a term.

Why do points from an AP always land on a straight line, but points from a GP never do?

It comes down to what kind of function of nn each formula is. An AP's explicit rule, tn=a+(n−1)dt_n=a+(n-1)d, is a linear function of nn — constant plus constant-times-nn — and the graph of any linear function is, by definition, a straight line. A GP's explicit rule, tn=a r n−1t_n=a\,r^{\,n-1}, is exponential in nn, since nn sits in the exponent, and exponential functions always curve, growing or shrinking faster and faster rather than by equal steps. This works as a diagnostic in reverse too: if a handful of plotted terms visibly curve rather than line up, the sequence cannot be an AP, whatever its formula looks like on paper.

Before this