Problem 17
Question
Solve each equation, where \(n \geq 0\). $$C(n, 0)=1$$
Step-by-Step Solution
Verified Answer
Given the equation \( C(n, 0) = 1 \) where \( n \geq 0 \), we apply the formula for binomial coefficients: \( C(n, k) = \frac{n!}{k!(n-k)!} \). For our case, we have:
\[
C(n, 0) = \frac{n!}{0!(n-0)!}.
\]
Since 0! is defined to be 1, and (n-0)! is simply n!, the equation simplifies to:
\[
C(n, 0) = \frac{n!}{n!} = 1.
\]
Thus, for any \( n \geq 0 \), the equation \( C(n, 0) = 1 \) holds true.
1Step 1: Definition of binomial coefficient
The binomial coefficient is defined as the number of ways to choose k elements from a set of n elements (referred to as "n choose k"), and is denoted by C(n, k). Mathematically, it can be expressed as:
\[
C(n, k) = \frac{n!}{k!(n-k)!},
\]
where n! stands for n factorial, the product of all positive integers up to n.
2Step 2: Solve for C(n, 0)
Now, we'll plug in the values for our given equation, \( C(n, 0) = 1 \):
\[
C(n, 0) = \frac{n!}{0!(n-0)!}.
\]
Since 0! is defined to be 1, and (n-0)! is simply n!, we can plug these values in and simplify:
\[
C(n, 0) = \frac{n!}{1 \cdot n!}.
\]
3Step 3: Final Step: Simplify and obtain the result
When we simplify the equation, we can cancel out the factorials:
\[
C(n, 0) = \frac{n!}{n!} = 1.
\]
Thus, for any \( n \geq 0 \), the equation \( C(n, 0) = 1 \) holds true.
Key Concepts
CombinatoricsFactorial NotationSolving Binomial EquationsPermutations and Combinations
Combinatorics
At its core, combinatorics is a branch of mathematics that deals with counting, both as a means and an end in obtaining results, and certain properties of finite structures. It is fundamental to various fields like algebra, probability, and geometry. For many students beginning to learn about combinatorics, it's essential to understand that it's the mathematical science of counting and arranging. Within combinatorics, we often work with problems that can be phrased in terms of 'how many different ways can we select or arrange some items?' This is often where the concept of binomial coefficients comes into play.
Combinatorics is largely about finding efficient ways to count without having to enumerate every possibility, which becomes virtually impossible for large sets. The principles of combinatorics are applied when we want to know the number of ways of choosing items from a collection (combinations), or how many permutations there are of a given number of objects.
Combinatorics is largely about finding efficient ways to count without having to enumerate every possibility, which becomes virtually impossible for large sets. The principles of combinatorics are applied when we want to know the number of ways of choosing items from a collection (combinations), or how many permutations there are of a given number of objects.
Factorial Notation
The factorial notation is key in combinatorics and other branches of mathematics. It is represented by an exclamation point (!) and means the product of all positive integers up to a given number. For instance, the factorial of 5 is denoted as 5! and is calculated as:
\[5! = 5 \times 4 \times 3 \times 2 \times 1 = 120.\]
The use of factorial notation simplifies the expression and calculation of large products, which are common in permutations and combinations. A peculiar and essential fact to note is that the factorial of zero (\(0!\)) is defined to be 1. This is not due to multiplication (as there are no numbers to multiply), but it is a convention that ensures the consistency and usefulness of the factorial concept, particularly in formulas involving binomial coefficients and combinations.
\[5! = 5 \times 4 \times 3 \times 2 \times 1 = 120.\]
The use of factorial notation simplifies the expression and calculation of large products, which are common in permutations and combinations. A peculiar and essential fact to note is that the factorial of zero (\(0!\)) is defined to be 1. This is not due to multiplication (as there are no numbers to multiply), but it is a convention that ensures the consistency and usefulness of the factorial concept, particularly in formulas involving binomial coefficients and combinations.
Solving Binomial Equations
A binomial equation typically refers to a polynomial equation involving two terms. However, when it comes to combinatorics, solving binomial equations involves understanding the binomial coefficient. As demonstrated in our initial problem, the equation \(C(n, 0) = 1\) is a simple form of a binomial equation where the binomial coefficient, often read as 'n choose 0', represents the number of ways to choose 0 elements from a set of n, which is always 1.
To solve more complex binomial coefficient equations, it's essential to grasp the general form of the coefficient, understanding that the numerator dictates the starting number of combinations' possibilities, and the denominator filters out the repeat combinations and adjustments for the number chosen (k). By manipulating these equations algebraically, and understanding the properties of factorials, solutions to binomial equations can be formalized.
To solve more complex binomial coefficient equations, it's essential to grasp the general form of the coefficient, understanding that the numerator dictates the starting number of combinations' possibilities, and the denominator filters out the repeat combinations and adjustments for the number chosen (k). By manipulating these equations algebraically, and understanding the properties of factorials, solutions to binomial equations can be formalized.
Permutations and Combinations
Understanding permutations and combinations is vital for solving problems that ask 'in how many ways' something can occur. They both deal with selecting items from a set and are closely related but are used under different conditions.
\[nPr = \frac{n!}{(n-r)!}.\]
This formula considers the many ways we can arrange a given number of objects from a larger set.
\[C(n, r) = \frac{n!}{r!(n-r)!}.\]
This formula is what's used to find our initial problem's solution involving the binomial coefficient. The fundamental distinction between permutations and combinations lies within the emphasis on order, which combinations disregard, hence having generally fewer combinations than permutations for the same number of items.
Permutations
This refers to the arrangement of all or part of a set of objects, where the order is important. The permutation of n distinct objects taken r at a time is denoted as \(nPr\) and is calculated by:\[nPr = \frac{n!}{(n-r)!}.\]
This formula considers the many ways we can arrange a given number of objects from a larger set.
Combinations
Combinations, on the other hand, refer to the selection of objects where order does not matter. The number of ways to choose r items from a set of n distinct items is denoted as \(C(n, r)\) or sometimes \(nCr\), and is given by:\[C(n, r) = \frac{n!}{r!(n-r)!}.\]
This formula is what's used to find our initial problem's solution involving the binomial coefficient. The fundamental distinction between permutations and combinations lies within the emphasis on order, which combinations disregard, hence having generally fewer combinations than permutations for the same number of items.
Other exercises in this chapter
Problem 17
Two cards are drawn at random from a standard deck of cards. Find the probability that: One is a club and the other a diamond.
View solution Problem 17
Using Exercises 13-16, predict the largest binomial coefficient in the expansion of \((x+y)^{n}.\)
View solution Problem 17
Find the number of two-digit numerals that can be formed using the digits \(2,3,5,6,\) and, 9 and that contain no repeated digits.
View solution Problem 18
Two cards are drawn at random successively from a standard deck. The first card is replaced before the second is drawn. Find the probability that: The first is
View solution