# You know from calculus that functions play a fundamental role in mathematics.

 To view this video please enable JavaScript, and consider upgrading to a web browser that supports HTML5 video
Save this PDF as:

Size: px
Start display at page:

Download "You know from calculus that functions play a fundamental role in mathematics."

## Transcription

1 CHPTER 12 Functions You know from calculus that functions play a fundamental role in mathematics. You likely view a function as a kind of formula that describes a relationship between two (or more) quantities. You certainly understand and appreciate the fact that relationships between quantities are important in all scientific disciplines, so you do not need to be convinced that functions are important. Still, you may not be aware of the full significance of functions. Functions are more than merely descriptions of numeric relationships. In a more general sense, functions can compare and relate different kinds of mathematical structures. You will see this as your understanding of mathematics deepens. In preparation of this deepening, we will now explore a more general and versatile view of functions. The concept of a relation between sets (Definition 11.7) plays a big role here, so you may want to quickly review it Functions Let s start on familiar ground. Consider the function f (x) = x 2 from R to R. Its graph is the set of points R = { (x, x 2 ) : x R } R R. R (x, x 2 ) x R Figure familiar function Having read Chapter 11, you may see f in a new light. Its graph R R R is a relation on the set R. In fact, as we shall see, functions are just special kinds of relations. efore stating the exact definition, we

2 Functions 197 look at another example. Consider the function f (n) = n + 2 that converts integers n into natural numbers n + 2. Its graph is R = { (n, n + 2) : n Z } Z N N Z Figure The function f : Z N, where f (n) = n + 2 Figure 12.2 shows the graph R as darkened dots in the grid of points Z N. Notice that in this example R is not a relation on a single set. The set of input values Z is different from the set N of output values, so the graph R Z N is a relation from Z to N. This example illustrates three things. First, a function can be viewed as sending elements from one set to another set. (In the case of f, = Z and = N.) Second, such a function can be regarded as a relation from to. Third, for every input value n, there is exactly one output value f (n). In your high school algebra course, this was expressed by the vertical line test: ny vertical line intersects a function s graph at most once. It means that for any input value x, the graph contains exactly one point of form (x, f (x)). Our main definition, given below, incorporates all of these ideas. Definition 12.1 Suppose and are sets. function f from to (denoted as f : ) is a relation f from to, satisfying the property that for each a the relation f contains exactly one ordered pair of form (a, b). The statement (a, b) f is abbreviated f (a) = b. Example 12.1 Consider the function f graphed in Figure ccording to Definition 12.1, we regard f as the set of points in its graph, that is, f = { (n, n + 2) : n Z } Z N. This is a relation from Z to N, and indeed given any a Z the set f contains exactly one ordered pair (a, a +2) whose first coordinate is a. Since (1,3) f, we write f (1) = 3; and since ( 3,5) f we write f ( 3) = 5, etc. In general, (a, b) f means that f sends the input

3 198 Functions value a to the output value b, and we express this as f (a) = b. This function can be expressed by a formula: For each input value n, the output value is n + 2, so we may write f (n) = n + 2. ll this agrees with the way we thought of functions in algebra and calculus; the only difference is that now we also think of a function as a relation. Definition 12.2 For a function f :, the set is called the domain of f. (Think of the domain as the set of possible input values for f.) The set is called the codomain of f. The range of f is the set { f (a) : a } = { } b : (a, b) f. (Think of the range as the set of all possible output values for f. Think of the codomain as a sort of target for the outputs.) Continuing Example 12.1, the domain of f is Z and its codomain is N. Its range is { f (a) : a Z } = { a + 2 : a Z } = { 2,3,4,5,... }. Notice that the range is a subset of the codomain, but it does not (in this case) equal the codomain. In our examples so far, the domains and codomains are sets of numbers, but this needn t be the case in general, as the next example indicates. Example 12.2 Let = { p, q, r, s } and = { 0,1,2 }, and f = { (p,0),(q,1),(r,2),(s,2) }. This is a function f : because each element of occurs exactly once as a first coordinate of an ordered pair in f. We have f (p) = 0, f (q) = 1, f (r) = 2 and f (s) = 2. The domain of f is { p, q, r, s }, and the codomain and range are both { 0,1,2 } (p,0) (p,1) (p,2) (q,0) (q,1) (q,2) (r,0) (r,1) (r,2) (s,0) (s,1) (s,2) p q r s s r q p (a) (b) Figure Two ways of drawing the function f = { (p,0),(q,1),(r,2),(s,2) }

4 Functions 199 If and are not both sets of numbers it can be difficult to draw a graph of f : in the traditional sense. Figure 12.3(a) shows an attempt at a graph of f from Example The sets and are aligned roughly as x- and y-axes, and the Cartesian product is filled in accordingly. The subset f is indicated with dashed lines, and this can be regarded as a graph of f. more natural visual description of f is shown in 12.3(b). The sets and are drawn side-by-side, and arrows point from a to b whenever f (a) = b. In general, if f : is the kind of function you may have encountered in algebra or calculus, then conventional graphing techniques offer the best visual description of it. On the other hand, if and are finite or if we are thinking of them as generic sets, then describing f with arrows is often a more appropriate way of visualizing it. We emphasize that, according to Definition 12.1, a function is really just a special kind of set. ny function f : is a subset of. y contrast, your calculus text probably defined a function as a certain kind of rule. While that intuitive outlook is adequate for the first few semesters of calculus, it does not hold up well to the rigorous mathematical standards necessary for further progress. The problem is that words like rule are too vague. Defining a function as a set removes the ambiguity. It makes a function into a concrete mathematical object. Still, in practice we tend to think of functions as rules. Given f : Z N where f (x) = x + 2, we think of this as a rule that associates any number n Z to the number n + 2 in N, rather than a set containing ordered pairs (n, n + 2). It is only when we have to understand or interpret the theoretical nature of functions (as we do in this text) that Definition 12.1 comes to bear. The definition is a foundation that gives us license to think about functions in a more informal way. The next example brings up a point about notation. Consider a function such as f : Z 2 Z, whose domain is a Cartesian product. This function takes as input an ordered pair (m, n) Z 2 and sends it to a number f ((m, n)) Z. To simplify the notation, it is common to write f (m, n) instead of f ((m, n)), even though this is like writing f x instead of f (x). We also remark that although we ve been using the letters f, g and h to denote functions, any other reasonable symbol could be used. Greek letters such as ϕ and θ are common. Example 12.3 Say a function ϕ : Z 2 Z is defined as ϕ(m, n) = 6m 9n. Note that as a set, this function is ϕ = {( (m, n),6m 9n ) : (m, n) Z 2} Z 2 Z. What is the range of ϕ?

5 200 Functions To answer this, first observe that for any (m, n) Z 2, the value f (m, n) = 6m 9n = 3(2m 3n) is a multiple of 3. Thus every number in the range is a multiple of 3, so the range is a subset of the set of all multiples of 3. On the other hand if b = 3k is a multiple of 3 we have ϕ( k, k) = 6( k) 9( k) = 3k = b, which means any multiple of 3 is in the range of ϕ. Therefore the range of ϕ is the set { 3k : k Z } of all multiples of 3. To conclude this section, let s use Definition 12.1 to help us understand what it means for two functions f : and g : C D to be equal. ccording to our definition, functions f and g are subsets f and g C D. It makes sense to say that f and g are equal if f = g, that is, if they are equal as sets. Thus the two functions f = { (1, a),(2, a),(3, b) } and g = { (3, b),(2, a),(1, a) } are equal because the sets f and g are equal. Notice that the domain of both functions is = { 1,2,3 }, the set of first elements x in the ordered pairs (x, y) f = g. In general, equal functions must have equal domains. Observe also that the equality f = g means f (x) = g(x) for every x. We repackage these ideas in the following definition. Definition 12.3 Two functions f : and g : D are equal if f (x) = g(x) for every x. Observe that f and g can have different codomains and still be equal. Consider the functions f : Z N and g : Z Z defined as f (x) = x + 2 and g(x) = x + 2. Even though their codomains are different, the functions are equal because f (x) = g(x) for every x in the domain. Exercises for Section Suppose = { 0,1,2,3,4 }, = { 2,3,4,5 } and f = { (0,3),(1,3),(2,4),(3,2),(4,2) }. State the domain and range of f. Find f (2) and f (1). 2. Suppose = { a, b, c, d }, = { 2,3,4,5,6 } and f = { (a,2),(b,3),(c,4),(d,5) }. State the domain and range of f. Find f (b) and f (d). 3. There are four different functions f : { a, b } { 0,1 }. List them all. Diagrams will suffice. 4. There are eight different functions f : { a, b, c } { 0,1 }. List them all. Diagrams will suffice. 5. Give an example of a relation from { a, b, c, d } to { d, e } that is not a function. 6. Suppose f : Z Z is defined as f = { (x,4x+5) : x Z }. State the domain, codomain and range of f. Find f (10).

6 Injective and Surjective Functions Consider the set f = { (x, y) Z Z : 3x + y = 4 }. Is this a function from Z to Z? Explain. 8. Consider the set f = { (x, y) Z Z : x + 3y = 4 }. Is this a function from Z to Z? Explain. 9. Consider the set f = { (x 2, x) : x R }. Is this a function from R to R? Explain. 10. Consider the set f = { (x 3, x) : x R }. Is this a function from R to R? Explain. 11. Is the set θ = { (X, X ) : X Z 5 } a function? If so, what is its domain and range? 12. Is the set θ = {( (x, y),(3y,2x, x + y) ) : x, y R } a function? If so, what is its domain, codomain and range? 12.2 Injective and Surjective Functions You may recall from algebra and calculus that a function may be oneto-one and onto, and these properties are related to whether or not the function is invertible. We now review these important ideas. In advanced mathematics, the word injective is often used instead of one-to-one, and surjective is used instead of onto. Here are the exact definitions: Definition 12.4 function f : is: 1. injective (or one-to-one) if for every x, y, x y implies f (x) f (y); 2. surjective (or onto) if for every b there is an a with f (a) = b; 3. bijective if f is both injective and surjective. elow is a visual description of Definition In essence, injective means that unequal elements in always get sent to unequal elements in. Surjective means that every element of has an arrow pointing to it, that is, it equals f (a) for some a in the domain of f. Injective means that for any two x, y, this happens... x y...and not this: x y Surjective means that for any b... b...this happens: a b

7 202 Functions For more concrete examples, consider the following functions from R to R. The function f (x) = x 2 is not injective because 2 2, but f ( 2) = f (2). Nor is it surjective, for if b = 1 (or if b is any negative number), then there is no a R with f (a) = b. On the other hand, g(x) = x 3 is both injective and surjective, so it is also bijective. There are four possible injective/surjective combinations that a function may possess. This is illustrated in the following figure showing four functions from to. Functions in the first column are injective, those in the second column are not injective. Functions in the first row are surjective, those in the second row are not. Surjective Not surjective Injective a 1 b 2 c 3 (bijective) a b Not injective a b c a 1 2 b 2 3 c 3 We note in passing that, according to the definitions, a function is surjective if and only if its codomain equals its range. Often it is necessary to prove that a particular function f : is injective. For this we must prove that for any two elements x, y, the conditional statement (x y) ( f (x) f (y) ) is true. The two main approaches for this are summarized below. How to show a function f : is injective: Direct approach: Suppose x, y and x y.. Therefore f (x) f (y). Contrapositive approach: Suppose x, y and f (x) = f (y).. Therefore x = y. Of these two approaches, the contrapositive is often the easiest to use, especially if f is defined by an algebraic formula. This is because the contrapositive approach starts with the equation f (x) = f (y) and proceeds

8 Injective and Surjective Functions 203 to the equation x = y. In algebra, as you know, it is usually easier to work with equations than inequalities. To prove that a function is not injective, you must disprove the statement (x y) ( f (x) f (y) ). For this it suffices to find example of two elements x, y for which x y and f (x) = f (y). Next we examine how to prove that f : is surjective. ccording to Definition 12.4, we must prove the statement b, a, f (a) = b. In words, we must show that for any b, there is at least one a (which may depend on b) having the property that f (a) = b. Here is an outline. How to show a function f : is surjective: Suppose b. [Prove there exists a for which f (a) = b.] In the second step, we have to prove the existence of an a for which f (a) = b. For this, just finding an example of such an a would suffice. (How to find such an example depends on how f is defined. If f is given as a formula, we may be able to find a by solving the equation f (a) = b for a. Sometimes you can find a by just plain common sense.) To show f is not surjective, we must prove the negation of b, a, f (a) = b, that is, we must prove b, a, f (a) b. The following examples illustrate these ideas. (For the first example, note that the set R { 0 } is R with the number 0 removed.) Example 12.4 Show that the function f : R { 0 } R defined as f (x) = 1 x +1 is injective but not surjective. We will use the contrapositive approach to show that f is injective. Suppose x, y R { 0 } and f (x) = f (y). This means 1 x + 1 = 1 y + 1. Subtracting 1 from both sides and inverting produces x = y. Therefore f is injective. Function f is not surjective because there exists an element b = 1 R for which f (x) = 1 x for every x R { 0 }. Example 12.5 Show that the function g : Z Z Z Z defined by the formula g(m, n) = (m + n, m + 2n), is both injective and surjective. We will use the contrapositive approach to show that g is injective. Thus we need to show that g(m, n) = g(k,l) implies (m, n) = (k,l). Suppose (m, n),(k,l) Z Z and g(m, n) = g(k,l). Then (m+n, m+2n) = (k+l, k+2l). It follows that m + n = k +l and m +2n = k +2l. Subtracting the first equation from the second gives n = l. Next, subtract n = l from m + n = k + l to get m = k. Since m = k and n = l, it follows that (m, n) = (k,l). Therefore g is injective.

9 204 Functions To see that g is surjective, consider an arbitrary element (b, c) Z Z. We need to show that there is some (x, y) Z Z for which g(x, y) = (b, c). To find (x, y), note that g(x, y) = (b, c) means (x + y, x + 2y) = (b, c). This leads to the following system of equations: x + y = b x + 2y = c. Solving gives x = 2b c and y = c b. Then (x, y) = (2b c, c b). We now have g(2b c, c b) = (b, c), and it follows that g is surjective. Example 12.6 Consider function h : Z Z Q defined as h(m, n) = m n + 1. Determine whether this is injective and whether it is surjective. This function is not injective because of the unequal elements (1, 2) and (1, 2) in Z Z for which h(1,2) = h(1, 2) = 1 3. However, h is surjective: Take any element b Q. Then b = c d for some c, d Z. Notice we may assume d is c positive by making c negative, if necessary. Then h(c, d 1) = d 1 +1 = c d = b. Exercises for Section Let = { 1,2,3,4 } and = { a, b, c }. Give an example of a function f : that is neither injective nor surjective. 2. Consider the logarithm function ln : (0, ) R. Decide whether this function is injective and whether it is surjective. 3. Consider the cosine function cos : R R. Decide whether this function is injective and whether it is surjective. What if it had been defined as cos : R [ 1,1]? 4. function f : Z Z Z is defined as f (n) = (2n, n + 3). Verify whether this function is injective and whether it is surjective. 5. function f : Z Z is defined as f (n) = 2n + 1. Verify whether this function is injective and whether it is surjective. 6. function f : Z Z Z is defined as f (m, n) = 3n 4m. Verify whether this function is injective and whether it is surjective. 7. function f : Z Z Z is defined as f (m, n) = 2n 4m. Verify whether this function is injective and whether it is surjective. 8. function f : Z Z Z Z is defined as f (m, n) = (m + n,2m + n). Verify whether this function is injective and whether it is surjective. 9. Prove that the function f : R { 2 } R { 5 } defined by f (x) = 5x + 1 is bijective. x Prove the function f : R { 1 } R { 1 } ( ) x defined by f (x) = is bijective. x Consider the function θ : { 0,1 } N Z defined as θ(a, b) = ( 1) a b. Is θ injective? Is it surjective? ijective? Explain.

10 The Pigeonhole Principle Consider the function θ : { 0,1 } N Z defined as θ(a, b) = a 2ab+b. Is θ injective? Is it surjective? ijective? Explain. 13. Consider the function f : R 2 R 2 defined by the formula f (x, y) = (xy, x 3 ). Is f injective? Is it surjective? ijective? Explain. 14. Consider the function θ : P(Z) P(Z) defined as θ(x) = X. Is θ injective? Is it surjective? ijective? Explain. 15. This question concerns functions f : {,,C, D, E, F,G } { 1,2,3,4,5,6,7 }. How many such functions are there? How many of these functions are injective? How many are surjective? How many are bijective? 16. This question concerns functions f : {,,C, D, E } { 1,2,3,4,5,6,7 }. How many such functions are there? How many of these functions are injective? How many are surjective? How many are bijective? 17. This question concerns functions f : {,,C, D, E, F,G } { 1,2 }. How many such functions are there? How many of these functions are injective? How many are surjective? How many are bijective? 18. Prove that the function f : N Z defined as f (n) = ( 1)n (2n 1) + 1 is bijective The Pigeonhole Principle Here is a simple but useful idea. Imagine there is a set of pigeons and a set of pigeon-holes, and all the pigeons fly into the pigeon-holes. You can think of this as describing a function f :, where pigeon X flies into pigeon-hole f (X). Figure 12.4 illustrates this. Pigeons f Pigeon-holes Pigeons f Pigeon-holes (a) (b) Figure The pigeonhole principle In Figure 12.4(a) there are more pigeons than pigeon-holes, and it is obvious that in such a case at least two pigeons have to fly into the same pigeon-hole, meaning that f is not injective. In Figure 12.4(b) there are fewer pigeons than pigeon-holes, so clearly at least one pigeon-hole remains empty, meaning that f is not surjective.

11 206 Functions lthough the underlying idea expressed by these figures has little to do with pigeons, it is nonetheless called the pigeonhole principle: The Pigeonhole Principle Suppose and are finite sets and f : is any function. Then: 1. If >, then f is not injective. 2. If <, then f is not surjective. Though the pigeonhole principle is obvious, it can be used to prove some things that are not so obvious. Example 12.7 Prove the following proposition. Proposition If is any set of 10 integers between 1 and 100, then there exist two different subsets X and Y for which the sum of elements in X equals the sum of elements in Y. To illustrate what this proposition is saying, consider the random set = { 5,7,12,11,17,50,51,80,90,100 } of 10 integers between 1 and 100. Notice that has subsets X = { 5,80 } and Y = { 7,11,17,50 } for which the sum of the elements in X equals the sum of those in Y. If we tried to mess up by changing the 5 to a 6, we get = { 6,7,12,11,17,50,51,80,90,100 } which has subsets X = { 7,12,17,50 } and Y = { 6,80 } both of whose elements add up to the same number (86). The proposition asserts that this is always possible, no matter what is. Here is a proof: Proof. Suppose { 1,2,3,4,...,99,100 } and = 10, as stated. Notice that if X, then X has no more than 10 elements, each between 1 and 100, and therefore the sum of all the elements of X is less than = Consider the function f : P() { 0,1,2,3,4,...,1000 } where f (X) is the sum of the elements in X. (Examples: f ({ 3,7,50 }) = 60; f ({ 1,70,80,95 }) = 246.) s P() = 2 10 = 1024 > 1001 = { 0,1,2,3,...,1000 }, it follows from the pigeonhole principle that f is not injective. Therefore there are two unequal sets X,Y P() for which f (X) = f (Y ). In other words, there are subsets X and Y for which the sum of elements in X equals the sum of elements in Y.

12 The Pigeonhole Principle 207 Example 12.8 Prove the following proposition. Proposition There are at least two Texans with the same number of hairs on their heads. Proof. We will use two facts. First, the population of Texas is more than twenty million. Second, it is a biological fact that every human head has fewer than one million hairs. Let be the set of all Texans, and let = { 0,1,2,3,4,..., }. Let f : be the function for which f (x) equals the number of hairs on the head of x. Since >, the pigeonhole principle asserts that f is not injective. Thus there are two Texans x and y for whom f (x) = f (y), meaning that they have the same number of hairs on their heads. Proofs that use the pigeonhole principle tend to be inherently nonconstructive, in the sense discussed in Section 7.4. For example, the above proof does not explicitly give us of two Texans with the same number of hairs on their heads; it only shows that two such people exist. If we were to make a constructive proof, we could find examples of two bald Texans. Then they have the same number of head hairs, namely zero. Exercises for Section Prove that if six numbers are chosen at random, then at least two of them will have the same remainder when divided by Prove that if a is a natural number, then there exist two unequal natural numbers k and l for which a k a l is divisible by Prove that if six natural numbers are chosen at random, then the sum or difference of two of them is divisible by Consider a square whose side-length is one unit. Select any five points from inside this square. Prove that at least two of these points are within 2 2 units of each other. 5. Prove that any set of seven distinct natural numbers contains a pair of numbers whose sum or difference is divisible by Given a sphere S, a great circle of S is the intersection of S with a plane through its center. Every great circle divides S into two parts. hemisphere is the union of the great circle and one of these two parts. Prove that if five points are placed arbitrarily on S, then there is a hemisphere that contains four of them. 7. Prove or disprove: ny subset X { 1,2,3,...,2n } with X > n contains two (unequal) elements a, b X for which a b or b a.

13 208 Functions 12.4 Composition You should be familiar with the notion of function composition from algebra and calculus. Still, it is worthwhile to revisit it now with our more sophisticated ideas about functions. Definition 12.5 Suppose f : and g : C are functions with the property that the codomain of f equals the domain of g. The composition of f with g is another function, denoted as g f and defined as follows: If x, then g f (x) = g(f (x)). Therefore g f sends elements of to elements of C, so g f : C. The following figure illustrates the definition. Here f :, g : C, and g f : C. We have, for example, g f (0) = g(f (0)) = g(2) = 4. e very careful with the order of the symbols. Even though g comes first in the symbol g f, we work out g f (x) as g(f (x)), with f acting on x first, followed by g acting on f (x) f g C g f C Figure Composition of two functions Notice that the composition g f also makes sense if the range of f is a subset of the domain of g. You should take note of this fact, but to keep matters simple we will continue to emphasize situations where the codomain of f equals the domain of g. Example 12.9 Suppose = { a, b, c }, = { 0,1 }, C = { 1,2,3 }. Let f : be the function f = { (a,0),(b,1),(c,0) }, and let g : C be the function g = { (0,3),(1,1) }. Then g f = { (a,3),(b,1),(c,3) }. Example Suppose = { a, b, c }, = { 0,1 }, C = { 1,2,3 }. Let f : be the function f = { (a,0),(b,1),(c,0) }, and let g : C be the function g = { (1,0),(2,1),(3,1) }. In this situation the composition g f is not defined because the codomain of f is not the same set as the domain C of g.

14 Composition 209 Remember: In order for g f to make sense, the codomain of f must equal the domain of g. (Or at least be a subset of it.) Example Let f : R R be defined as f (x) = x 2 + x, and g : R R be defined as g(x) = x + 1. Then g f : R R is the function defined by the formula g f (x) = g(f (x)) = g(x 2 + x) = x 2 + x + 1. Since the domains and codomains of g and f are the same, we can in this case do a composition in the other order. Note that f g : R R is the function defined as f g (x) = f (g(x)) = f (x + 1) = (x + 1) 2 + (x + 1) = x 2 + 3x + 2. This example illustrates that even when g f and f g are both defined, they are not necessarily equal. We can express this fact by saying function composition is not commutative. We close this section by proving several facts about function composition that you are likely to encounter in your future study of mathematics. First, we note that, although it is not commutative, function composition is associative. Theorem 12.1 Composition of functions is associative. That is if f :, g : C and h : C D, then (h g) f = h (g f ). Proof. Suppose f, g, h are as stated. It follows from Definition 12.5 that both (h g) f and h (g f ) are functions from to D. To show that they are equal, we just need to show ( ) ( ) (h g) f (x) = h (g f ) (x) for every x. Note that Definition 12.5 yields ( ) (h g) f (x) = (h g)(f (x)) = h(g(f (x)). lso ( ) h (g f ) (x) = h(g f (x)) = h(g(f (x))). Thus ( ) ( ) (h g) f (x) = h (g f ) (x), as both sides equal h(g(f (x))). Theorem 12.2 Suppose f : and g : C. If both f and g are injective, then g f is injective. If both f and g are surjective, then g f is surjective.

15 210 Functions Proof. First suppose both f and g are injective. To see that g f is injective, we must show that g f (x) = g f (y) implies x = y. Suppose g f (x) = g f (y). This means g(f (x)) = g(f (y)). It follows that f (x) = f (y). (For otherwise g wouldn t be injective.) ut since f (x) = f (y) and f is injective, it must be that x = y. Therefore g f is injective. Next suppose both f and g are surjective. To see that g f is surjective, we must show that for any element c C, there is a corresponding element a for which g f (a) = c. Thus consider an arbitrary c C. ecause g is surjective, there is an element b for which g(b) = c. nd because f is surjective, there is an element a for which f (a) = b. Therefore g(f (a)) = g(b) = c, which means g f (a) = c. Thus g f is surjective. Exercises for Section Suppose = { 5,6,8 }, = { 0,1 }, C = { 1,2,3 }. Let f : be the function f = { (5,1),(6,0),(8,1) }, and g : C be g = { (0,1),(1,1) }. Find g f. 2. Suppose = { 1,2,3,4 }, = { 0,1,2 }, C = { 1,2,3 }. Let f : be f = { (1,0),(2,1),(3,2),(4,0) }, and g : C be g = { (0,1),(1,1),(2,3) }. Find g f. 3. Suppose = { 1,2,3 }. Let f : be the function f = { (1,2),(2,2),(3,1) }, and let g : be the function g = { (1,3),(2,1),(3,2) }. Find g f and f g. 4. Suppose = { a, b, c }. Let f : be the function f = { (a, c),(b, c),(c, c) }, and let g : be the function g = { (a, a),(b, b),(c, a) }. Find g f and f g. 5. Consider the functions f, g : R R defined as f (x) = 3 x + 1 and g(x) = x 3. Find the formulas for g f and f g. 6. Consider the functions f, g : R R defined as f (x) = 1 the formulas for g f and f g. x 2 +1 and g(x) = 3x + 2. Find 7. Consider the functions f, g : Z Z Z Z defined as f (m, n) = (mn, m 2 ) and g(m, n) = (m + 1, m + n). Find the formulas for g f and f g. 8. Consider the functions f, g : Z Z Z Z defined as f (m, n) = (3m 4n,2m + n) and g(m, n) = (5m + n, m). Find the formulas for g f and f g. 9. Consider the functions f : Z Z Z defined as f (m, n) = m + n and g : Z Z Z defined as g(m) = (m, m). Find the formulas for g f and f g. 10. Consider the function f : R 2 R 2 defined by the formula f (x, y) = (xy, x 3 ). Find a formula for f f.

16 Inverse Functions Inverse Functions You may recall from calculus that if a function f is injective and surjective, then it has an inverse function f 1 that undoes the effect of f in the sense that f 1 (f (x)) = x for every x in the domain. (For example, if f (x) = x 3, then f 1 (x) = 3 x.) We now review these ideas. Our approach uses two ingredients, outlined in the following definitions. Definition 12.6 Given a set, the identity function on is the function i : defined as i (x) = x for every x. Example: If = { 1,2,3 }, then i = { (1,1),(2,2),(3,3) }. lso i Z = { (n, n) : n Z }. The identity function on a set is the function that sends any element of the set to itself. Notice that for any set, the identity function i is bijective: It is injective because i (x) = i (y) immediately reduces to x = y. It is surjective because if we take any element b in the codomain, then b is also in the domain, and i (b) = b. Definition 12.7 Given a relation R from to, the inverse relation of R is the relation from to defined as R 1 = { (y, x) : (x, y) R }. In other words, the inverse of R is the relation R 1 obtained by interchanging the elements in every ordered pair in R. For example, let = { a, b, c } and = { 1,2,3 }, and suppose f is the relation f = { (a,2),(b,3),(c,1) } from to. Then f 1 = { (2, a),(3, b),(1, c) } and this is a relation from to. Notice that f is actually a function from to, and f 1 is a function from to. These two relations are drawn below. Notice the drawing for relation f 1 is just the drawing for f with arrows reversed. a 1 a 1 b 2 b 2 c 3 c 3 f = { (a,2),(b,3),(c,1) } f 1 = { (2, a),(3, b),(1, c) } For another example, let and be the same sets as above, but consider the relation g = { (a,2),(b,3),(c,3) } from to. Then g 1 = { (2, a),(3, b),(3, c) } is a relation from to. These two relations are sketched below.

17 212 Functions a 1 a 1 b 2 b 2 c 3 c 3 g = { (a,2),(b,3),(c,3) } g 1 = { (2, a),(3, b),(3, c) } This time, even though the relation g is a function, its inverse g 1 is not a function because the element 3 occurs twice as a first coordinate of an ordered pair in g 1. In the above examples, relations f and g are both functions, and f 1 is a function and g 1 is not. This raises a question: What properties does f have and g lack that makes f 1 a function and g 1 not a function? The answer is not hard to see. Function g is not injective because g(b) = g(c) = 3, and thus (b,3) and (c,3) are both in g. This causes a problem with g 1 because it means (3, b) and (3, c) are both in g 1, so g 1 can t be a function. Thus, in order for g 1 to be a function, it would be necessary that g be injective. ut that is not enough. Function g also fails to be surjective because no element of is sent to the element 1. This means g 1 contains no ordered pair whose first coordinate is 1, so it can t be a function from to. If g 1 were to be a function it would be necessary that g be surjective. The previous two paragraphs suggest that if g is a function, then it must be bijective in order for its inverse relation g 1 to be a function. Indeed, this is easy to verify. Conversely, if a function is bijective, then its inverse relation is easily seen to be a function. We summarize this in the following theorem. Theorem 12.3 Let f : be a function. Then f is bijective if and only if the inverse relation f 1 is a function from to. Suppose f : is bijective, so according to the theorem f 1 is a function. Observe that the relation f contains all the pairs (x, f (x)) for x, so f 1 contains all the pairs (f (x), x). ut (f (x), x) f 1 means f 1 (f (x)) = x. Therefore f 1 f (x) = x for every x. From this we get f 1 f = i. Similar reasoning produces f f 1 = i. This leads to the following definitions. Definition 12.8 If f : is bijective then its inverse is the function f 1 :. Functions f and f 1 obey the equations f 1 f = i and f f 1 = i.

18 Inverse Functions 213 You probably recall from algebra and calculus at least one technique for computing the inverse of a bijective function f : to find f 1, start with the equation y = f (x). Then interchange variables to get x = f (y). Solving this equation for y (if possible) produces y = f 1 (x). The next two examples illustrate this. Example Find its inverse. The function f : R R defined as f (x) = x is bijective. We begin by writing y = x Now interchange variables to obtain x = y Solving for y produces y = 3 x 1. Thus f 1 (x) = 3 x 1. (You can check your answer by computing f 1 (f (x)) = 3 f (x) 1 = 3 x = x. Therefore f 1 (f (x)) = x. ny answer other than x indicates a mistake.) We close with one final example. Example 12.5 showed that the function g : Z Z Z Z defined by the formula g(m, n) = (m + n, m + 2n) is bijective. Let s find its inverse. The approach outlined above should work, but we need to be careful to keep track of coordinates in Z Z. We begin by writing (x, y) = g(m, n), then interchanging the variables (x, y) and (m, n) to get (m, n) = g(x, y). This gives (m, n) = (x + y, x + 2y), from which we get the following system of equations: x + y = m x + 2y = n. Solving this system using techniques from algebra with which you are familiar, we get x = 2m n y = n m. Then (x, y) = (2m n, n m), so g 1 (m, n) = (2m n, n m).

19 214 Functions We can check our work by confirming that g 1 (g(m, n)) = (m, n). Doing the math, g 1 (g(m, n)) = g 1 (m + n, m + 2n) = ( 2(m + n) (m + 2n),(m + 2n) (m + n) ) = (m, n). Exercises for Section Check that the function f : Z Z defined by f (n) = 6 n is bijective. Then compute f In Exercise 9 of Section 12.2 you proved that f : R { 2 } R { 5 } defined by f (x) = 5x + 1 is bijective. Now find its inverse. x 2 3. Let = { 2 n : n Z } = {..., 1 4, 1 2,1,2,4,8,...}. Show that the function f : Z defined as f (n) = 2 n is bijective. Then find f The function f : R (0, ) defined as f (x) = e x3 +1 is bijective. Find its inverse. 5. The function f : R R defined as f (x) = πx e is bijective. Find its inverse. 6. The function f : Z Z Z Z defined by the formula f (m, n) = (5m + 4n,4m + 3n) is bijective. Find its inverse. 7. Show that the function f : R 2 R 2 defined by the formula f (x, y) = ((x 2 + 1)y, x 3 ) is bijective. Then find its inverse. 8. Is the function θ : P(Z) P(Z) defined as θ(x) = X bijective? If so, what is its inverse? 9. Consider the function f : R N N R defined as f (x, y) = (y,3xy). Check that this is bijective; find its inverse. 10. Consider f : N Z defined as f (n) = ( 1)n (2n 1) + 1. This function is bijective 4 by Exercise 18 in Section Find its inverse Image and Preimage It is time to take up a matter of notation that you will encounter in future mathematics classes. Suppose we have a function f :. If X, the expression f (X) has a special meaning. It stands for the set { f (x) : x X }. Similarly, if Y then f 1 (Y ) has a meaning even if f is not invertible. The expression f 1 (Y ) stands for the set { x : f (x) Y }. Here are the precise definitions.

20 Image and Preimage 215 Definition 12.9 Suppose f : is a function. 1. If X, the image of X is the set f (X) = { f (x) : x X }. 2. If Y, the preimage of Y is the set f 1 (Y ) = { x : f (x) Y }. In words, the image f (X) of X is the set of all things in that f sends elements of X to. (Roughly speaking, you might think of f (X) as a kind of distorted copy or image of X in.) The preimage f 1 (Y ) of Y is the set of all things in that f sends into Y. Maybe you have already encountered these ideas in linear algebra, in a setting involving a linear transformation T : V W between two vector spaces. If X V is a subspace of V, then its image T(X) is a subspace of W. If Y W is a subspace of W, then its preimage T 1 (Y ) is a subspace of V. (If this does not sound familiar, then ignore it.) Example Let f : { s, t, u, v, w, x, y, z } { 0,1,2,3,4,5,6,7,8,9 }, where f = { (s,4),(t,8),(u,8),(v,1),(w,2),(x,4),(y,6),(z,4) }. Notice that f is neither injective nor surjective, so it certainly is not invertible. e sure you understand the following statements. 1. f ({ s, t, u, z }) = { 8,4 } 2. f ({ s, x, z }) = { 4 } 3. f ({ s, v, w, y }) = { 1,2,4,6 } 4. f 1({ 4 }) = { s, x, z } 5. f 1({ 4,9 }) = { s, x, z } 6. f 1({ 9 }) = 7. f 1({ 1,4,8 }) = { s, t, u, v, x, z } It is important to realize that the X and Y in Definition 12.9 are subsets (not elements!) of and. Note that in the above example we had f 1({ 4 }) = { s, x, z }, while f 1 (4) has absolutely no meaning because the inverse function f 1 does not exist. Likewise, there is a subtle difference between f ({ s }) = { 4 } and f (s) = 4. e careful. Example Consider the function f : R R defined as f (x) = x 2. Note that f ({ 0,1,2 }) = { 0,1,4 } and f 1({ 0,1,4 }) = { 2, 1,0,1,2 }. This shows f 1 (f (X)) X in general. Using the same f, now check your understanding of the following statements involving images and preimages of intervals: f ([ 2, 3]) = [0, 9], and f 1 ([0,9]) = [ 3,3]. lso f (R) = [0, ) and f 1 ([ 2, 1]) =.

### Sets and functions. {x R : x > 0}.

Sets and functions 1 Sets The language of sets and functions pervades mathematics, and most of the important operations in mathematics turn out to be functions or to be expressible in terms of functions.

### 1 The Concept of a Mapping

Arkansas Tech University MATH 4033: Elementary Modern Algebra Dr. Marcel B. Finan 1 The Concept of a Mapping The concept of a mapping (aka function) is important throughout mathematics. We have been dealing

### MAT2400 Analysis I. A brief introduction to proofs, sets, and functions

MAT2400 Analysis I A brief introduction to proofs, sets, and functions In Analysis I there is a lot of manipulations with sets and functions. It is probably also the first course where you have to take

### It is time to prove some theorems. There are various strategies for doing

CHAPTER 4 Direct Proof It is time to prove some theorems. There are various strategies for doing this; we now examine the most straightforward approach, a technique called direct proof. As we begin, it

### This chapter is all about cardinality of sets. At first this looks like a

CHAPTER Cardinality of Sets This chapter is all about cardinality of sets At first this looks like a very simple concept To find the cardinality of a set, just count its elements If A = { a, b, c, d },

### Students in their first advanced mathematics classes are often surprised

CHAPTER 8 Proofs Involving Sets Students in their first advanced mathematics classes are often surprised by the extensive role that sets play and by the fact that most of the proofs they encounter are

### INTRODUCTORY SET THEORY

M.Sc. program in mathematics INTRODUCTORY SET THEORY Katalin Károlyi Department of Applied Analysis, Eötvös Loránd University H-1088 Budapest, Múzeum krt. 6-8. CONTENTS 1. SETS Set, equal sets, subset,

### ( ) which must be a vector

MATH 37 Linear Transformations from Rn to Rm Dr. Neal, WKU Let T : R n R m be a function which maps vectors from R n to R m. Then T is called a linear transformation if the following two properties are

### Introducing Functions

Functions 1 Introducing Functions A function f from a set A to a set B, written f : A B, is a relation f A B such that every element of A is related to one element of B; in logical notation 1. (a, b 1

### Mathematics Review for MS Finance Students

Mathematics Review for MS Finance Students Anthony M. Marino Department of Finance and Business Economics Marshall School of Business Lecture 1: Introductory Material Sets The Real Number System Functions,

### Sets and Cardinality Notes for C. F. Miller

Sets and Cardinality Notes for 620-111 C. F. Miller Semester 1, 2000 Abstract These lecture notes were compiled in the Department of Mathematics and Statistics in the University of Melbourne for the use

### Cartesian Products and Relations

Cartesian Products and Relations Definition (Cartesian product) If A and B are sets, the Cartesian product of A and B is the set A B = {(a, b) :(a A) and (b B)}. The following points are worth special

### December 4, 2013 MATH 171 BASIC LINEAR ALGEBRA B. KITCHENS

December 4, 2013 MATH 171 BASIC LINEAR ALGEBRA B KITCHENS The equation 1 Lines in two-dimensional space (1) 2x y = 3 describes a line in two-dimensional space The coefficients of x and y in the equation

### Chapter 7. Functions and onto. 7.1 Functions

Chapter 7 Functions and onto This chapter covers functions, including function composition and what it means for a function to be onto. In the process, we ll see what happens when two dissimilar quantifiers

### Mathematics Course 111: Algebra I Part IV: Vector Spaces

Mathematics Course 111: Algebra I Part IV: Vector Spaces D. R. Wilkins Academic Year 1996-7 9 Vector Spaces A vector space over some field K is an algebraic structure consisting of a set V on which are

### 2. Methods of Proof Types of Proofs. Suppose we wish to prove an implication p q. Here are some strategies we have available to try.

2. METHODS OF PROOF 69 2. Methods of Proof 2.1. Types of Proofs. Suppose we wish to prove an implication p q. Here are some strategies we have available to try. Trivial Proof: If we know q is true then

### vertex, 369 disjoint pairwise, 395 disjoint sets, 236 disjunction, 33, 36 distributive laws

Index absolute value, 135 141 additive identity, 254 additive inverse, 254 aleph, 466 algebra of sets, 245, 278 antisymmetric relation, 387 arcsine function, 349 arithmetic sequence, 208 arrow diagram,

### Lecture 16 : Relations and Functions DRAFT

CS/Math 240: Introduction to Discrete Mathematics 3/29/2011 Lecture 16 : Relations and Functions Instructor: Dieter van Melkebeek Scribe: Dalibor Zelený DRAFT In Lecture 3, we described a correspondence

### A Second Course in Mathematics Concepts for Elementary Teachers: Theory, Problems, and Solutions

A Second Course in Mathematics Concepts for Elementary Teachers: Theory, Problems, and Solutions Marcel B. Finan Arkansas Tech University c All Rights Reserved First Draft February 8, 2006 1 Contents 25

### Sets and set operations: cont. Functions.

CS 441 Discrete Mathematics for CS Lecture 8 Sets and set operations: cont. Functions. Milos Hauskrecht milos@cs.pitt.edu 5329 Sennott Square Set Definition: set is a (unordered) collection of objects.

### Basic Concepts of Point Set Topology Notes for OU course Math 4853 Spring 2011

Basic Concepts of Point Set Topology Notes for OU course Math 4853 Spring 2011 A. Miller 1. Introduction. The definitions of metric space and topological space were developed in the early 1900 s, largely

### Math 313 Lecture #10 2.2: The Inverse of a Matrix

Math 1 Lecture #10 2.2: The Inverse of a Matrix Matrix algebra provides tools for creating many useful formulas just like real number algebra does. For example, a real number a is invertible if there is

### 1 Sets and Set Notation.

LINEAR ALGEBRA MATH 27.6 SPRING 23 (COHEN) LECTURE NOTES Sets and Set Notation. Definition (Naive Definition of a Set). A set is any collection of objects, called the elements of that set. We will most

### Mathematics for Computer Science/Software Engineering. Notes for the course MSM1F3 Dr. R. A. Wilson

Mathematics for Computer Science/Software Engineering Notes for the course MSM1F3 Dr. R. A. Wilson October 1996 Chapter 1 Logic Lecture no. 1. We introduce the concept of a proposition, which is a statement

### CARDINALITY, COUNTABLE AND UNCOUNTABLE SETS PART ONE

CARDINALITY, COUNTABLE AND UNCOUNTABLE SETS PART ONE With the notion of bijection at hand, it is easy to formalize the idea that two finite sets have the same number of elements: we just need to verify

### Math Review. for the Quantitative Reasoning Measure of the GRE revised General Test

Math Review for the Quantitative Reasoning Measure of the GRE revised General Test www.ets.org Overview This Math Review will familiarize you with the mathematical skills and concepts that are important

### SETS, RELATIONS, AND FUNCTIONS

September 27, 2009 and notations Common Universal Subset and Power Set Cardinality Operations A set is a collection or group of objects or elements or members (Cantor 1895). the collection of the four

### Module MA1S11 (Calculus) Michaelmas Term 2016 Section 3: Functions

Module MA1S11 (Calculus) Michaelmas Term 2016 Section 3: Functions D. R. Wilkins Copyright c David R. Wilkins 2016 Contents 3 Functions 43 3.1 Functions between Sets...................... 43 3.2 Injective

### Notes on Factoring. MA 206 Kurt Bryan

The General Approach Notes on Factoring MA 26 Kurt Bryan Suppose I hand you n, a 2 digit integer and tell you that n is composite, with smallest prime factor around 5 digits. Finding a nontrivial factor

### CHAPTER 5: MODULAR ARITHMETIC

CHAPTER 5: MODULAR ARITHMETIC LECTURE NOTES FOR MATH 378 (CSUSM, SPRING 2009). WAYNE AITKEN 1. Introduction In this chapter we will consider congruence modulo m, and explore the associated arithmetic called

### Understanding Basic Calculus

Understanding Basic Calculus S.K. Chung Dedicated to all the people who have helped me in my life. i Preface This book is a revised and expanded version of the lecture notes for Basic Calculus and other

### To define function and introduce operations on the set of functions. To investigate which of the field properties hold in the set of functions

Chapter 7 Functions This unit defines and investigates functions as algebraic objects. First, we define functions and discuss various means of representing them. Then we introduce operations on functions

### Sets, Relations and Functions

Sets, Relations and Functions Eric Pacuit Department of Philosophy University of Maryland, College Park pacuit.org epacuit@umd.edu ugust 26, 2014 These notes provide a very brief background in discrete

### Applications of Methods of Proof

CHAPTER 4 Applications of Methods of Proof 1. Set Operations 1.1. Set Operations. The set-theoretic operations, intersection, union, and complementation, defined in Chapter 1.1 Introduction to Sets are

### NOTES ON CATEGORIES AND FUNCTORS

NOTES ON CATEGORIES AND FUNCTORS These notes collect basic definitions and facts about categories and functors that have been mentioned in the Homological Algebra course. For further reading about category

### Section 1.1. Introduction to R n

The Calculus of Functions of Several Variables Section. Introduction to R n Calculus is the study of functional relationships and how related quantities change with each other. In your first exposure to

### MATH Fundamental Mathematics II.

MATH 10032 Fundamental Mathematics II http://www.math.kent.edu/ebooks/10032/fun-math-2.pdf Department of Mathematical Sciences Kent State University December 29, 2008 2 Contents 1 Fundamental Mathematics

### ORDERS OF ELEMENTS IN A GROUP

ORDERS OF ELEMENTS IN A GROUP KEITH CONRAD 1. Introduction Let G be a group and g G. We say g has finite order if g n = e for some positive integer n. For example, 1 and i have finite order in C, since

### The last three chapters introduced three major proof techniques: direct,

CHAPTER 7 Proving Non-Conditional Statements The last three chapters introduced three major proof techniques: direct, contrapositive and contradiction. These three techniques are used to prove statements

### Problem Set 1 Solutions Math 109

Problem Set 1 Solutions Math 109 Exercise 1.6 Show that a regular tetrahedron has a total of twenty-four symmetries if reflections and products of reflections are allowed. Identify a symmetry which is

### 5 =5. Since 5 > 0 Since 4 7 < 0 Since 0 0

a p p e n d i x e ABSOLUTE VALUE ABSOLUTE VALUE E.1 definition. The absolute value or magnitude of a real number a is denoted by a and is defined by { a if a 0 a = a if a

### Chapter 1 Section 5: Equations and Inequalities involving Absolute Value

Introduction The concept of absolute value is very strongly connected to the concept of distance. The absolute value of a number is that number s distance from 0 on the number line. Since distance is always

### Chapter 14. Transformations

Chapter 14 Transformations Questions For Thought 1. When you take a picture, how does the real world image become a reduced celluloid or digital image? 2. How are maps of the Earth made to scale? 3. How

### THREE DIMENSIONAL GEOMETRY

Chapter 8 THREE DIMENSIONAL GEOMETRY 8.1 Introduction In this chapter we present a vector algebra approach to three dimensional geometry. The aim is to present standard properties of lines and planes,

### This chapter describes set theory, a mathematical theory that underlies all of modern mathematics.

Appendix A Set Theory This chapter describes set theory, a mathematical theory that underlies all of modern mathematics. A.1 Basic Definitions Definition A.1.1. A set is an unordered collection of elements.

### Section 1. Statements and Truth Tables. Definition 1.1: A mathematical statement is a declarative sentence that is true or false, but not both.

M3210 Supplemental Notes: Basic Logic Concepts In this course we will examine statements about mathematical concepts and relationships between these concepts (definitions, theorems). We will also consider

### Finite Sets. Theorem 5.1. Two non-empty finite sets have the same cardinality if and only if they are equivalent.

MATH 337 Cardinality Dr. Neal, WKU We now shall prove that the rational numbers are a countable set while R is uncountable. This result shows that there are two different magnitudes of infinity. But we

### 136 CHAPTER 4. INDUCTION, GRAPHS AND TREES

136 TER 4. INDUCTION, GRHS ND TREES 4.3 Graphs In this chapter we introduce a fundamental structural idea of discrete mathematics, that of a graph. Many situations in the applications of discrete mathematics

### LECTURE 1 I. Inverse matrices We return now to the problem of solving linear equations. Recall that we are trying to find x such that IA = A

LECTURE I. Inverse matrices We return now to the problem of solving linear equations. Recall that we are trying to find such that A = y. Recall: there is a matri I such that for all R n. It follows that

### 3. Recurrence Recursive Definitions. To construct a recursively defined function:

3. RECURRENCE 10 3. Recurrence 3.1. Recursive Definitions. To construct a recursively defined function: 1. Initial Condition(s) (or basis): Prescribe initial value(s) of the function.. Recursion: Use a

### Mathematics for Economics (Part I) Note 5: Convex Sets and Concave Functions

Natalia Lazzati Mathematics for Economics (Part I) Note 5: Convex Sets and Concave Functions Note 5 is based on Madden (1986, Ch. 1, 2, 4 and 7) and Simon and Blume (1994, Ch. 13 and 21). Concave functions

### LEARNING OBJECTIVES FOR THIS CHAPTER

CHAPTER 2 American mathematician Paul Halmos (1916 2006), who in 1942 published the first modern linear algebra book. The title of Halmos s book was the same as the title of this chapter. Finite-Dimensional

### Section 4.3 Image and Inverse Image of a Set

Section 43 Image and Inverse Image of a Set Purpose of Section: To introduce the concept of the image and inverse image of a set We show that unions of sets are preserved under a mapping whereas only one-to-one

### Linear Algebra Notes for Marsden and Tromba Vector Calculus

Linear Algebra Notes for Marsden and Tromba Vector Calculus n-dimensional Euclidean Space and Matrices Definition of n space As was learned in Math b, a point in Euclidean three space can be thought of

### CHAPTER 2. Inequalities

CHAPTER 2 Inequalities In this section we add the axioms describe the behavior of inequalities (the order axioms) to the list of axioms begun in Chapter 1. A thorough mastery of this section is essential

### INTRODUCTION TO PROOFS: HOMEWORK SOLUTIONS

INTRODUCTION TO PROOFS: HOMEWORK SOLUTIONS STEVEN HEILMAN Contents 1. Homework 1 1 2. Homework 2 6 3. Homework 3 10 4. Homework 4 16 5. Homework 5 19 6. Homework 6 21 7. Homework 7 25 8. Homework 8 28

### LINEAR ALGEBRA W W L CHEN

LINEAR ALGEBRA W W L CHEN c W W L Chen, 1997, 2008 This chapter is available free to all individuals, on understanding that it is not to be used for financial gain, and may be downloaded and/or photocopied,

### Common Curriculum Map. Discipline: Math Course: College Algebra

Common Curriculum Map Discipline: Math Course: College Algebra August/September: 6A.5 Perform additions, subtraction and multiplication of complex numbers and graph the results in the complex plane 8a.4a

### 1 VECTOR SPACES AND SUBSPACES

1 VECTOR SPACES AND SUBSPACES What is a vector? Many are familiar with the concept of a vector as: Something which has magnitude and direction. an ordered pair or triple. a description for quantities such

### It is not immediately obvious that this should even give an integer. Since 1 < 1 5

Math 163 - Introductory Seminar Lehigh University Spring 8 Notes on Fibonacci numbers, binomial coefficients and mathematical induction These are mostly notes from a previous class and thus include some

### MBA Jump Start Program

MBA Jump Start Program Module 2: Mathematics Thomas Gilbert Mathematics Module Online Appendix: Basic Mathematical Concepts 2 1 The Number Spectrum Generally we depict numbers increasing from left to right

### UNIT 2 MATRICES - I 2.0 INTRODUCTION. Structure

UNIT 2 MATRICES - I Matrices - I Structure 2.0 Introduction 2.1 Objectives 2.2 Matrices 2.3 Operation on Matrices 2.4 Invertible Matrices 2.5 Systems of Linear Equations 2.6 Answers to Check Your Progress

### Geometric Transformations

Geometric Transformations Definitions Def: f is a mapping (function) of a set A into a set B if for every element a of A there exists a unique element b of B that is paired with a; this pairing is denoted

### GROUPS ACTING ON A SET

GROUPS ACTING ON A SET MATH 435 SPRING 2012 NOTES FROM FEBRUARY 27TH, 2012 1. Left group actions Definition 1.1. Suppose that G is a group and S is a set. A left (group) action of G on S is a rule for

### Recall that two vectors in are perpendicular or orthogonal provided that their dot

Orthogonal Complements and Projections Recall that two vectors in are perpendicular or orthogonal provided that their dot product vanishes That is, if and only if Example 1 The vectors in are orthogonal

### 1 if 1 x 0 1 if 0 x 1

Chapter 3 Continuity In this chapter we begin by defining the fundamental notion of continuity for real valued functions of a single real variable. When trying to decide whether a given function is or

### In mathematics there are endless ways that two entities can be related

CHAPTER 11 Relations In mathematics there are endless ways that two entities can be related to each other. Consider the following mathematical statements. 5 < 10 5 5 6 = 30 5 5 80 7 > 4 x y 8 3 a b ( mod

### Linear Codes. In the V[n,q] setting, the terms word and vector are interchangeable.

Linear Codes Linear Codes In the V[n,q] setting, an important class of codes are the linear codes, these codes are the ones whose code words form a sub-vector space of V[n,q]. If the subspace of V[n,q]

### LAKE ELSINORE UNIFIED SCHOOL DISTRICT

LAKE ELSINORE UNIFIED SCHOOL DISTRICT Title: PLATO Algebra 1-Semester 2 Grade Level: 10-12 Department: Mathematics Credit: 5 Prerequisite: Letter grade of F and/or N/C in Algebra 1, Semester 2 Course Description:

### NOTES ON LINEAR TRANSFORMATIONS

NOTES ON LINEAR TRANSFORMATIONS Definition 1. Let V and W be vector spaces. A function T : V W is a linear transformation from V to W if the following two properties hold. i T v + v = T v + T v for all

### Basic Properties of Rings

Basic Properties of Rings A ring is an algebraic structure with an addition operation and a multiplication operation. These operations are required to satisfy many (but not all!) familiar properties. Some

### Writing proofs. Tim Hsu, San José State University. Revised February Sets, elements, and the if-then method 11

Writing proofs Tim Hsu, San José State University Revised February 2016 Contents I Fundamentals 5 1 Definitions and theorems 5 2 What is a proof? 5 3 A word about definitions 6 II The structure of proofs

### A set is a Many that allows itself to be thought of as a One. (Georg Cantor)

Chapter 4 Set Theory A set is a Many that allows itself to be thought of as a One. (Georg Cantor) In the previous chapters, we have often encountered sets, for example, prime numbers form a set, domains

### 1. R In this and the next section we are going to study the properties of sequences of real numbers.

+a 1. R In this and the next section we are going to study the properties of sequences of real numbers. Definition 1.1. (Sequence) A sequence is a function with domain N. Example 1.2. A sequence of real

### MATH REVIEW KIT. Reproduced with permission of the Certified General Accountant Association of Canada.

MATH REVIEW KIT Reproduced with permission of the Certified General Accountant Association of Canada. Copyright 00 by the Certified General Accountant Association of Canada and the UBC Real Estate Division.

### 3. Equivalence Relations. Discussion

3. EQUIVALENCE RELATIONS 33 3. Equivalence Relations 3.1. Definition of an Equivalence Relations. Definition 3.1.1. A relation R on a set A is an equivalence relation if and only if R is reflexive, symmetric,

### Chapter 1 Quadratic Equations in One Unknown (I)

Tin Ka Ping Secondary School 015-016 F. Mathematics Compulsory Part Teaching Syllabus Chapter 1 Quadratic in One Unknown (I) 1 1.1 Real Number System A Integers B nal Numbers C Irrational Numbers D Real

### Classical Analysis I

Classical Analysis I 1 Sets, relations, functions A set is considered to be a collection of objects. The objects of a set A are called elements of A. If x is an element of a set A, we write x A, and if

### FOUNDATIONS OF ALGEBRAIC GEOMETRY CLASS 22

FOUNDATIONS OF ALGEBRAIC GEOMETRY CLASS 22 RAVI VAKIL CONTENTS 1. Discrete valuation rings: Dimension 1 Noetherian regular local rings 1 Last day, we discussed the Zariski tangent space, and saw that it

### MATH 55: HOMEWORK #2 SOLUTIONS

MATH 55: HOMEWORK # SOLUTIONS ERIC PETERSON * 1. SECTION 1.5: NESTED QUANTIFIERS 1.1. Problem 1.5.8. Determine the truth value of each of these statements if the domain of each variable consists of all

### WHAT ARE MATHEMATICAL PROOFS AND WHY THEY ARE IMPORTANT?

WHAT ARE MATHEMATICAL PROOFS AND WHY THEY ARE IMPORTANT? introduction Many students seem to have trouble with the notion of a mathematical proof. People that come to a course like Math 216, who certainly

Mathematics 0N1 Solutions 1 1. Write the following sets in list form. 1(i) The set of letters in the word banana. {a, b, n}. 1(ii) {x : x 2 + 3x 10 = 0}. 3(iv) C A. True 3(v) B = {e, e, f, c}. True 3(vi)

### MATHEMATICS (CLASSES XI XII)

MATHEMATICS (CLASSES XI XII) General Guidelines (i) All concepts/identities must be illustrated by situational examples. (ii) The language of word problems must be clear, simple and unambiguous. (iii)

### Geometry Unit 1. Basics of Geometry

Geometry Unit 1 Basics of Geometry Using inductive reasoning - Looking for patterns and making conjectures is part of a process called inductive reasoning Conjecture- an unproven statement that is based

### CORRELATED TO THE SOUTH CAROLINA COLLEGE AND CAREER-READY FOUNDATIONS IN ALGEBRA

We Can Early Learning Curriculum PreK Grades 8 12 INSIDE ALGEBRA, GRADES 8 12 CORRELATED TO THE SOUTH CAROLINA COLLEGE AND CAREER-READY FOUNDATIONS IN ALGEBRA April 2016 www.voyagersopris.com Mathematical

### Lecture 10: Invertible matrices. Finding the inverse of a matrix

Lecture 10: Invertible matrices. Finding the inverse of a matrix Danny W. Crytser April 11, 2014 Today s lecture Today we will Today s lecture Today we will 1 Single out a class of especially nice matrices

### Applications of Trigonometry

chapter 6 Tides on a Florida beach follow a periodic pattern modeled by trigonometric functions. Applications of Trigonometry This chapter focuses on applications of the trigonometry that was introduced

### MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS

MATRIX ALGEBRA AND SYSTEMS OF EQUATIONS Systems of Equations and Matrices Representation of a linear system The general system of m equations in n unknowns can be written a x + a 2 x 2 + + a n x n b a

### Chapter 3. Cartesian Products and Relations. 3.1 Cartesian Products

Chapter 3 Cartesian Products and Relations The material in this chapter is the first real encounter with abstraction. Relations are very general thing they are a special type of subset. After introducing

### Homework One Solutions. Keith Fratus

Homework One Solutions Keith Fratus June 8, 011 1 Problem One 1.1 Part a In this problem, we ll assume the fact that the sum of two complex numbers is another complex number, and also that the product

### Euclidean Geometry. We start with the idea of an axiomatic system. An axiomatic system has four parts:

Euclidean Geometry Students are often so challenged by the details of Euclidean geometry that they miss the rich structure of the subject. We give an overview of a piece of this structure below. We start

### Lecture 17 : Equivalence and Order Relations DRAFT

CS/Math 240: Introduction to Discrete Mathematics 3/31/2011 Lecture 17 : Equivalence and Order Relations Instructor: Dieter van Melkebeek Scribe: Dalibor Zelený DRAFT Last lecture we introduced the notion

### MPE Review Section III: Logarithmic & Exponential Functions

MPE Review Section III: Logarithmic & Eponential Functions FUNCTIONS AND GRAPHS To specify a function y f (, one must give a collection of numbers D, called the domain of the function, and a procedure

### Vector Spaces II: Finite Dimensional Linear Algebra 1

John Nachbar September 2, 2014 Vector Spaces II: Finite Dimensional Linear Algebra 1 1 Definitions and Basic Theorems. For basic properties and notation for R N, see the notes Vector Spaces I. Definition

### 26 Integers: Multiplication, Division, and Order

26 Integers: Multiplication, Division, and Order Integer multiplication and division are extensions of whole number multiplication and division. In multiplying and dividing integers, the one new issue

### discuss how to describe points, lines and planes in 3 space.

Chapter 2 3 Space: lines and planes In this chapter we discuss how to describe points, lines and planes in 3 space. introduce the language of vectors. discuss various matters concerning the relative position

### SUBGROUPS OF CYCLIC GROUPS. 1. Introduction In a group G, we denote the (cyclic) group of powers of some g G by

SUBGROUPS OF CYCLIC GROUPS KEITH CONRAD 1. Introduction In a group G, we denote the (cyclic) group of powers of some g G by g = {g k : k Z}. If G = g, then G itself is cyclic, with g as a generator. Examples