Powers functions. Composition and Inverse of functions.

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Chapter 4 Powers functions. Composition and Inverse of functions. 4.1 Power functions We have already encountered some examples of power functions in the previous chapters, in the context of polynomial and rational functions: indeed, functions such as as power functions. More generally speaking, power functions are defined as follows: Definition: Examples: Power functions are fairly ubiquitous in natural systems, and in many examples, the power is not an integer. We will now work through a case study that showcases power functions in the context of socioeconomics. 4.1.1 Case Study: The Rank-Size law of cities A remarkable empirical law of socio-economics is the observed relationship between the rank and size of the population of each city in a given country. To construct a graph showing this relationship, simply graph the population of a city against its rank (i.e. 1 for largest, 2 for second largest, 3 for third largest, etc..). Here are two examples, one for the US, and one for France: 59

60 CHAPTER 4. POWERS FUNCTIONS. COMPOSITION AND INVERSE OF FUNCTIONS. Size (Millions) 9 8 7 6 5 4 3 2 1 0 0 10 20 30 40 50 60 70 80 90 100 Rank France US Unfortunately, the graph is not as informative as we would like, mostly because the population of the largest cities is so much larger than that of the smaller ones. An alternative way of plotting the data is to use a log-log scale. We will learn more about them in a few lecture s time, but just note for now how, on each axis, the numbers 1, 10, 100, etc. are equally-spaced, instead of the numbers 1,2,3,... being equally spaced. When using a log-log plot, something remarkable happens to this data: 10 France US Size (Millions) 1 0.1 0.01 1 10 100 Rank As we will learn shortly, when data falls on a straight line in a log-log plot, this is symptomatic of a power-law relationship. It is in fact how scientists prove that a relationship is a power law. Let s try to fit the data with a function of the kind s = f(r) = ar b, where s is the size, and r is the rank: we get

4.1. POWER FUNCTIONS 61 Using these two functions, we therefore see that the 20th largest cities in France and the US have population size of about We will now learn a little more about power laws, both in terms of where they occur, and what we can do with them. 4.1.2 More examples of power laws in nature There are many examples of power laws in nature. Some of the most common ones are geometric relationships such as : Another common class of power laws are allometric laws in biology: In fact, there are examples of power laws in most fields of Science!

62 CHAPTER 4. POWERS FUNCTIONS. COMPOSITION AND INVERSE OF FUNCTIONS. 4.1.3 Manipulations of power functions The following rules of exponents apply for manipulating power functions: 4.1.4 Graphs of power functions The overall shape of the graph of a power function depends on the sign and value of the exponent b, as well as the number a of in front of course.

4.2. INVERSE OF FUNCTIONS AND COMPOSITION OF FUNCTIONS 63 4.2 Inverse of functions and Composition of functions Textbook section 4.2 4.2.1 Case Study: The Rank-Size law of cities Sacramento is the capital of California, and has a population size of about 490,000 people. What is its rank based on the graph? This is in fact a fairly good estimate, as the true rank of Sacramento is We can apply the same technique to many cities on this graph, i.e. look up their rank based on their size. We could in fact create a graph with this information, which would allow us to retrieve it and share it with others much more efficiently. This would give the following plot (on a log-log scale): 100 US Cities Rank 10 1 100000 1x10 6 1x10 7 Size (Million) Now, what about Santa Cruz? The population of Santa Cruz is roughly 70,000 people, so what is its rank? Unfortunately, the graph above is not very useful because it does not show what happens for cities of less than 200,000 people. So what can we do? The solution here is not to use the graph, but to use what we know about the Rank-Size relationship of US cities: In fact, we could do this for any US city, namely, to get an estimate of the rank as a function of their size:

64 CHAPTER 4. POWERS FUNCTIONS. COMPOSITION AND INVERSE OF FUNCTIONS. In doing so, we have created another function g(s), which takes the size and returns the rank: r = g(s). If we plot this new function on the graph of Rank vs. Size, we see that it indeed fits the data very well. We can therefore use this, as an alternative option to the graph, to find the estimated rank of any city in the US knowing its size! The functions f and g are clearly related to one another: In fact, they are called Inverse of on another! We will now learn more about inverses, and generalize the concept we have just learned. 4.2.2 Definition of the inverse, and examples Definition: Graphical interpretation:

4.2. INVERSE OF FUNCTIONS AND COMPOSITION OF FUNCTIONS 65 Examples y = f(x) = 3x + 2: y = f(x) = x 2 (for x 0): y = f(x) = x 2 (for x 2): y = f(x) = 3x+1 x 2 Important notes:

66 CHAPTER 4. POWERS FUNCTIONS. COMPOSITION AND INVERSE OF FUNCTIONS. 4.2.3 Graph of an inverse function and horizontal line test: Example 1: y = f(x) = 3x + 2 Example 2: y = f(x) = x 2 So from these graphs we notice that:

4.2. INVERSE OF FUNCTIONS AND COMPOSITION OF FUNCTIONS 67 Note: It may happen that through this process, the graph of the inverse does not satisfy the vertical line test: in that case, the inverse is not defined. Horizontal line test: To verify that the inverse of a function is unique, we check that the function satisfies the horizontal line test: When a function f(x) does not satisfy the horizontal line test, we can often choose a smaller domain for which the inverse is unique. Example: for the function f(x) = x 2, we saw earlier that the inverse of f(x) = x 2 is defined provided we select only the interval for which x 0. In this interval, the function f(x) does satisfy the horizontal line test.

68 CHAPTER 4. POWERS FUNCTIONS. COMPOSITION AND INVERSE OF FUNCTIONS. 4.2.4 Composition of functions Knowing that if y = f(x), then x = f 1 (y), we can come to a rather interesting conclusion: While this may have seemed to be a simple game of plugging one thing into another, the notion of applying a function to another function is actually a very important mathematical concept, called the composition of two functions. Examples: f(x) = sin(x), g(x) = 4x 1: f g: f(x) = 1 x 2 2, g(x) = x + 1: f g: f(x) = 1 x, g(x) = x 2 : g f: Important note: Changing the order of the composition yields an entirely different function! Example: f(x) = x, g(x) = x 2 + 1 f g:

4.2. INVERSE OF FUNCTIONS AND COMPOSITION OF FUNCTIONS 69 g f: 4.2.5 The composition of a function and its inverse As we found out above, there are two fundamental relationships between a function and its inverse: We can check that this is true in all the examples we have seen before: