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Honors Pre-Calculus Unit 11 Review: Sequences, Probability & Counting Theory

This unit covers number patterns and the math of counting, from arithmetic and geometric sequences to permutations, combinations and probability. By the end, you should be able to write a formula for a sequence, add up a series quickly, count outcomes without listing them, and turn those counts into probabilities.

Read the overview first, then work through each topic note and try the checkpoint question before you look at its answer.

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What is Honors Pre-Calculus unit 11?

Unit 11 is about replacing tedious listing and adding with formulas. You'll write rules for sequences, sum them with sigma notation, and count arrangements and selections. Then you'll use those counts to expand binomials and compute probabilities.

Honors Pre-Calculus Unit 11 covers sequences and their notation (explicit and recursive formulas, factorials), arithmetic sequences with a common difference, geometric sequences with a common ratio, and series written in sigma notation, including finite arithmetic and geometric sums and infinite geometric sums. The second half covers counting: the addition and multiplication principles, permutations, combinations and subsets. It then applies them to the binomial theorem with Pascal's triangle and to probability, including complements, unions of events and independent events. Exact topics vary by school, but this sequence-to-probability path is the typical version.

A sequence is a function whose inputs are the term numbers 1, 2, 3, and so on.

An arithmetic sequence adds the same amount each step, so it behaves like a linear function. A geometric sequence multiplies by the same amount each step, so it behaves like an exponential function. Recognizing which one you have tells you which formula to use.

A series is the sum of a sequence's terms, and formulas let you skip the adding.

Sigma notation packs a long sum into one expression. Arithmetic and finite geometric series have closed-form sum formulas. An infinite geometric series with a nonzero first term has a finite sum only when ∣r∣<1|r| < 1. An all-zero series has sum 0.

Counting tells you how many outcomes exist, and probability measures how likely an event is.

The multiplication principle, permutations and combinations let you count outcomes without writing them all down. When outcomes are equally likely, probability is the number of favorable outcomes divided by the total. Combinations also appear as the coefficients in the binomial theorem.

Find the structure in a pattern so you never have to list everything out.

Every topic here trades brute force for a formula. You find the 100th term without writing 99 others, sum 50 terms without adding them, and count a million license plates without listing one. The skill is spotting the structure (a constant difference, a constant ratio, whether order matters) and matching it to the right formula.

Honors Pre-Calculus unit 11 topics

11.6

Binomial Theorem

For a nonnegative integer n, the binomial theorem expands (x + y)^n without multiplying it out by hand:

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Unit 11 review notes

11.1

Sequences and Their Notations

A sequence is an ordered list of numbers, called terms, that follows a rule. The notation ana_n means the term in position nn, so a1a_1 is the first term and a10a_{10} is the tenth. A finite sequence stops after some number of terms, and an infinite sequence keeps going.

There are two ways to describe the rule. An explicit formula gives ana_n directly from nn. With an=3n−1a_n = 3n - 1, plug in n=10n = 10 and you get a10=29a_{10} = 29 right away.

A recursive formula defines a term using earlier terms. For example, an=an−1+3a_n = a_{n-1} + 3 with a1=2a_1 = 2 gives the same sequence 2, 5, 8, 11, .... To find the tenth term by applying this rule repeatedly, calculate the earlier terms first. A recursive formula always needs a starting value, or it can't produce anything. The Fibonacci sequence 1, 1, 2, 3, 5, 8, ... is recursive with two starting values, since each term is the sum of the previous two.

Factorials show up here and again later in the unit. The notation n!n! means n⋅(n−1)⋯2⋅1n \cdot (n-1) \cdots 2 \cdot 1, so 4!=244! = 24. By definition, 0!=10! = 1.

A sequence is a function whose inputs are positive integers, so its graph is a set of separate dots, not a connected curve.

  • Explicit formula: A rule that gives any term ana_n directly from its position nn.
  • Recursive formula: A rule that defines each term using one or more earlier terms, together with starting values.
  • Factorial: The product n!=n(n−1)⋯2⋅1n! = n(n-1)\cdots 2 \cdot 1, with 0!=10! = 1 by definition.

Check yourself: Write the first four terms of an=2an−1+1a_n = 2a_{n-1} + 1 with a1=3a_1 = 3. (Answer: 3, 7, 15, 31)

11.2

Arithmetic Sequences

An arithmetic sequence adds the same number, the common difference dd, to get from each term to the next. You find it by subtracting consecutive terms, d=an+1−and = a_{n+1} - a_n. If the differences aren't all equal, the sequence isn't arithmetic. A positive dd makes the sequence increase, and a negative dd makes it decrease.

The recursive form is an=an−1+da_n = a_{n-1} + d. The explicit form is an=a1+(n−1)da_n = a_1 + (n-1)d. The n−1n - 1 is there because the first term has had zero differences added to it.

Arithmetic sequences are linear functions in disguise. For an=5+(n−1)(4)a_n = 5 + (n-1)(4), simplifying gives an=4n+1a_n = 4n + 1, a line with slope 4. The common difference plays the role of the slope, which is why the graph of the terms is a set of dots along a straight line.

Worked example. An arithmetic sequence has a4=17a_4 = 17 and a10=41a_{10} = 41. Find a30a_{30}. Going from term 4 to term 10 takes 6 steps, so 6d=41−17=246d = 41 - 17 = 24 and d=4d = 4. Work backward 3 steps from a4a_4 to get a1=17−3(4)=5a_1 = 17 - 3(4) = 5. Then a30=5+(30−1)(4)=5+116=121a_{30} = 5 + (30 - 1)(4) = 5 + 116 = 121.

  • Common difference: The constant amount dd added to each term of an arithmetic sequence to get the next term.
  • Arithmetic explicit formula: The formula an=a1+(n−1)da_n = a_1 + (n-1)d, which gives any term of an arithmetic sequence.

Check yourself: Is 4, 9, 15, 22, ... arithmetic? (Answer: No. The differences are 5, 6 and 7, which are not constant.)

11.3

Geometric Sequences

A geometric sequence multiplies each term by the same number, the common ratio rr, to get the next term. You can find it by dividing consecutive terms, r=an+1anr = \dfrac{a_{n+1}}{a_n}, when an≠0a_n \neq 0. The recursive form is an=r⋅an−1a_n = r \cdot a_{n-1}, and the explicit form is an=a1rn−1a_n = a_1 r^{n-1}. If r=0r = 0, use a1a_1 for the first term and 0 for every later term.

The exponent is n−1n - 1, not nn. The first term has been multiplied by rr zero times, and r0=1r^0 = 1. For example, with a1=2a_1 = 2 and r=3r = 3, a10=2⋅39=2⋅19,683=39,366a_{10} = 2 \cdot 3^9 = 2 \cdot 19{,}683 = 39{,}366.

The value of rr controls the behavior of a geometric sequence with a nonzero first term.

  • If ∣r∣>1|r| > 1, the terms grow in magnitude, like 2, 6, 18, 54.
  • If ∣r∣<1|r| < 1, the terms approach 0, like 8, 4, 2, 1. The sequence converges to 0.
  • If rr is negative, the signs alternate. With r=−2r = -2, you get 1, -2, 4, -8.

Geometric sequences with positive ratios follow exponential patterns and can model compound interest, population growth and half-life decay. Arithmetic sequences add a fixed amount, while geometric sequences multiply by a fixed factor. A negative ratio produces alternating signs rather than an ordinary real exponential function.

  • Common ratio: The constant factor rr that each term of a geometric sequence is multiplied by to get the next term.
  • Geometric explicit formula: The formula an=a1rn−1a_n = a_1 r^{n-1}, which gives any term of a geometric sequence.
  • Convergent sequence: A sequence whose terms approach a single fixed value as nn gets larger.

Check yourself: Find rr and a6a_6 for 162, 54, 18, ... (Answer: r=13r = \frac{1}{3}, and a6=162(13)5=162243=23a_6 = 162\left(\frac{1}{3}\right)^5 = \frac{162}{243} = \frac{2}{3})

FeatureArithmetic sequenceGeometric sequence
Step from term to termAdd $d$Multiply by $r$
How to find the constant$d = a_{n+1} - a_n$$r = a_{n+1} / a_n$ when $a_n \neq 0$
Recursive formula$a_n = a_{n-1} + d$$a_n = r \cdot a_{n-1}$
Explicit formula$a_n = a_1 + (n-1)d$$a_n = a_1 r^{n-1}$
Matching function typeLinearExponential when $r > 0$
Example3, 7, 11, 15 ($d = 4$)3, 6, 12, 24 ($r = 2$)
11.4

Series and Their Notations

A series is the sum of the terms of a sequence. Sigma notation writes it compactly. In ∑k=152k\sum_{k=1}^{5} 2k, the index kk starts at the lower limit 1, stops at the upper limit 5, and you add the outputs to get 2+4+6+8+10=302 + 4 + 6 + 8 + 10 = 30. The sum of the first nn terms is called a partial sum, SnS_n.

Three sum formulas do most of the work in this topic.

  • Arithmetic series use Sn=n2(a1+an)S_n = \frac{n}{2}(a_1 + a_n), which is the average of the first and last terms times the number of terms.
  • Finite geometric series use Sn=a1(1−rn)1−rS_n = \dfrac{a_1(1 - r^n)}{1 - r} for r≠1r \neq 1.
  • Infinite geometric series use S∞=a11−rS_\infty = \dfrac{a_1}{1 - r} when ∣r∣<1|r| < 1. If a1≠0a_1 \neq 0 and ∣r∣≥1|r| \geq 1, the terms do not approach 0, so the series diverges. If a1=0a_1 = 0, every term is 0 and the sum is 0.

Worked example. Add the integers from 1 to 100. This is arithmetic with n=100n = 100, a1=1a_1 = 1 and a100=100a_{100} = 100, so S100=1002(1+100)=50(101)=5050S_{100} = \frac{100}{2}(1 + 100) = 50(101) = 5050.

Worked example. Find 12+4+43+⋯12 + 4 + \frac{4}{3} + \cdots. Here a1=12a_1 = 12 and r=13r = \frac{1}{3}. Since ∣r∣<1|r| < 1, the sum exists, and S∞=121−13=122/3=18S_\infty = \dfrac{12}{1 - \frac{1}{3}} = \dfrac{12}{2/3} = 18.

  • Sigma notation: A way to write a sum using ∑\sum, an index, a lower limit, an upper limit and a general term.
  • Partial sum: The sum SnS_n of the first nn terms of a sequence.
  • Divergent series: An infinite series whose partial sums don't approach a finite number.

Check yourself: Evaluate ∑k=14(k2+1)\sum_{k=1}^{4} (k^2 + 1). (Answer: 2+5+10+17=342 + 5 + 10 + 17 = 34)

11.5

Counting Principles

Counting principles let you find how many outcomes exist without listing them. The addition principle handles "or" choices that can't happen together. If you pick one item from 5 shirts or 3 hats, you have 5+3=85 + 3 = 8 choices. The multiplication principle handles "and" choices made in stages. A shirt and a hat give 5×3=155 \times 3 = 15 outfits.

Permutations count arrangements where order matters. Arranging all nn distinct objects gives n!n! ways, and arranging rr of them gives P(n,r)=n!(n−r)!P(n, r) = \dfrac{n!}{(n-r)!}.

Combinations count selections where order doesn't matter, using C(n,r)=(nr)=n!r!(n−r)!C(n, r) = \binom{n}{r} = \dfrac{n!}{r!(n-r)!}. Each group of rr items can be ordered r!r! ways, so C(n,r)=P(n,r)r!C(n, r) = \dfrac{P(n, r)}{r!}.

Worked example. A club has 10 members. Electing a president, vice president and secretary means the positions are different, so order matters, and P(10,3)=10⋅9⋅8=720P(10, 3) = 10 \cdot 9 \cdot 8 = 720. Picking a 3-person committee means order doesn't matter, so C(10,3)=7203!=120C(10, 3) = \dfrac{720}{3!} = 120.

Two extra cases come up often. When letters repeat, divide by the factorial of each repeat count, so BOOK has 4!2!=12\dfrac{4!}{2!} = 12 arrangements. A set with nn elements has 2n2^n subsets, counting the empty set, because each element is either in or out.

  • Multiplication principle: If the first choice has mm options and each first choice allows nn second choices, making both choices gives m×nm \times n outcomes.
  • Permutation: An arrangement of objects in which order matters, counted by P(n,r)=n!(n−r)!P(n, r) = \frac{n!}{(n-r)!}.
  • Combination: A selection of objects in which order doesn't matter, counted by (nr)=n!r!(n−r)!\binom{n}{r} = \frac{n!}{r!(n-r)!}.

Check yourself: How many 4-digit PINs are possible if digits can repeat? (Answer: 10×10×10×10=10,00010 \times 10 \times 10 \times 10 = 10{,}000)

Question to askPermutationCombination
Does order matter?YesNo
Formula$\frac{n!}{(n-r)!}$$\frac{n!}{r!(n-r)!}$
Typical wordingArrange, rank, assign roles, line upChoose, select, form a group or committee
10 people, pick 3720 (president, VP, secretary)120 (a committee of 3)
11.6

Binomial Theorem

For a nonnegative integer nn, the binomial theorem expands (x+y)n(x + y)^n without multiplying it out by hand:

(x+y)n=∑k=0n(nk)xn−kyk(x + y)^n = \sum_{k=0}^{n} \binom{n}{k} x^{n-k} y^k

The expansion has n+1n + 1 terms. The power on xx counts down from nn, the power on yy counts up from 0, and in every term the two powers add to nn. For example, (a+b)3=a3+3a2b+3ab2+b3(a + b)^3 = a^3 + 3a^2b + 3ab^2 + b^3.

The coefficients (nk)\binom{n}{k} are the same combinations from counting. You can also read them off Pascal's triangle. After the top 1, each entry is the sum of the two entries above it, with missing entries treated as 0. Row 4 (counting the top row as row 0) is 1, 4, 6, 4, 1, which gives the coefficients of (x+y)4(x + y)^4.

With a subtraction like (a−b)n(a - b)^n, treat it as (a+(−b))n(a + (-b))^n and the signs will alternate.

Worked example. Find the 4th term of (3x−2y)6(3x - 2y)^6. The 4th term uses k=3k = 3, because counting starts at k=0k = 0. The coefficient is (63)=20\binom{6}{3} = 20. The term is 20(3x)3(−2y)3=20⋅27x3⋅(−8y3)=−4320x3y320(3x)^3(-2y)^3 = 20 \cdot 27x^3 \cdot (-8y^3) = -4320x^3y^3.

  • Binomial coefficient: The number (nk)\binom{n}{k} that multiplies xn−kykx^{n-k}y^k in the expansion of (x+y)n(x + y)^n.
  • Pascal's triangle: A triangle of numbers that starts with 1. Each later entry is the sum of the two entries above it, treating missing entries as 0. Row nn lists the coefficients of (x+y)n(x + y)^n.

Check yourself: What is the coefficient of x2x^2 in (x+3)5(x + 3)^5? (Answer: The x2x^2 term uses k=3k = 3, so the coefficient is (53)⋅33=10⋅27=270\binom{5}{3} \cdot 3^3 = 10 \cdot 27 = 270.)

11.7

Probability

Probability measures how likely an event is on a scale from 0 to 1. An impossible event has probability 0, and a certain event has probability 1. The sample space is the set of all possible outcomes, and an event is a subset of it. When every outcome is equally likely, P(E)=favorable outcomestotal outcomesP(E) = \dfrac{\text{favorable outcomes}}{\text{total outcomes}}. On a fair die, P(even)=36=12P(\text{even}) = \frac{3}{6} = \frac{1}{2}. Counting methods from 11.5 often supply both numbers. The chance of drawing 2 aces from a deck is (42)(522)=61326=1221\dfrac{\binom{4}{2}}{\binom{52}{2}} = \dfrac{6}{1326} = \dfrac{1}{221}.

A few rules handle most problems.

  • The complement rule says P(not A)=1−P(A)P(\text{not } A) = 1 - P(A).
  • For "A or B," use P(A∪B)=P(A)+P(B)−P(A∩B)P(A \cup B) = P(A) + P(B) - P(A \cap B). You subtract the overlap so it isn't counted twice. If the events are mutually exclusive, the overlap is 0.
  • For independent events, where one doesn't affect the other, P(A∩B)=P(A)⋅P(B)P(A \cap B) = P(A) \cdot P(B).

Worked example. Find the probability of at least one 6 in four rolls of a fair die. Counting "at least one" directly is messy, so use the complement. The chance of no 6 on one roll is 56\frac{5}{6}, and the rolls are independent, so P(no 6s)=(56)4=6251296≈0.482P(\text{no 6s}) = \left(\frac{5}{6}\right)^4 = \frac{625}{1296} \approx 0.482. That makes P(at least one 6)≈1−0.482=0.518P(\text{at least one 6}) \approx 1 - 0.482 = 0.518.

  • Sample space: The set of all possible outcomes of an experiment.
  • Mutually exclusive events: Events that can't happen at the same time, so P(A∩B)=0P(A \cap B) = 0.
  • Independent events: Events where one happening doesn't change the probability of the other, so P(A∩B)=P(A)P(B)P(A \cap B) = P(A)P(B).

Check yourself: What is the probability of drawing a heart or a king from a standard 52-card deck? (Answer: 1352+452−152=1652=413\frac{13}{52} + \frac{4}{52} - \frac{1}{52} = \frac{16}{52} = \frac{4}{13})

Key terms

TermDefinition
SequenceAn ordered list of numbers that follows a rule, written with terms $a_1, a_2, a_3, \ldots$
Common differenceThe constant $d$ added to each term of an arithmetic sequence to get the next term.
Common ratioThe constant $r$ that each term of a geometric sequence is multiplied by to get the next term.
SeriesThe sum of the terms of a sequence, often written in sigma notation.
PermutationAn ordered arrangement of objects, counted by $\frac{n!}{(n-r)!}$ when choosing $r$ of $n$ objects.
CombinationAn unordered selection of objects, counted by $\binom{n}{r} = \frac{n!}{r!(n-r)!}$.
Binomial theoremThe formula $(x + y)^n = \sum_{k=0}^{n} \binom{n}{k} x^{n-k} y^k$ for expanding a binomial raised to a whole-number power.
Sample spaceThe set of every possible outcome of an experiment.
ComplementThe event that A does not happen, with probability $1 - P(A)$.

Mistakes to avoid in Sequences, Probability & Counting Theory

Using $n$ instead of $n - 1$ in the term formulas

The explicit formulas are an=a1+(n−1)da_n = a_1 + (n-1)d and an=a1rn−1a_n = a_1 r^{n-1}, because the first term has had zero steps applied. Plug in n=1n = 1 to check that your formula gives back a1a_1. Watch out for the geometric sum formula, Sn=a1(1−rn)1−rS_n = \frac{a_1(1 - r^n)}{1 - r}, which does use rnr^n, since it counts nn terms.

Mixing up permutations and combinations

Ask whether swapping two chosen items creates a different outcome. If it does, as with ranks, roles or seat order, use a permutation. If the group is the same either way, as with committees or pizza toppings, use a combination, which divides out the r!r! orderings.

Using the infinite sum formula when $|r| \geq 1$

The expression a11−r\frac{a_1}{1 - r} is undefined at r=1r = 1 and can give a misleading number for other values. For example, if a1>0a_1 > 0 and r=2r = 2, it gives a negative number even though the terms are positive. Check ∣r∣<1|r| < 1 before using the sum formula. If ∣r∣≥1|r| \geq 1 and a1≠0a_1 \neq 0, the series diverges. If a1=0a_1 = 0, its sum is 0.

Adding probabilities of events that overlap

Adding P(A)+P(B)P(A) + P(B) only works when A and B can't both happen. For hearts or kings, simple addition counts the king of hearts twice, so subtract P(A∩B)P(A \cap B). For independent events, multiply P(A)P(A) by P(B)P(B). For dependent events, use the conditional probability instead: P(A∩B)=P(A)P(B∣A)P(A \cap B) = P(A)P(B \mid A).

Study unit 11 other ways

Ready to review Unit 11?Start with the notes, check the topic cards, and use the practice or resource links when they are available for this course.