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Dice Simulation. It is often useful to be able to simulate the throw of a fair die. Write a MATLAB function dice that simulates the throw of a fair die by returning some random integer between 1 and 6 every time that it is called. (Hint: Call randomo to generate a randem number. Divide the possible values out of random0 into six equal intervals, and return the number of the interval that a given random value falls into.)

Short Answer

Expert verified
To create a MATLAB function called 'dice' that simulates the throw of a fair die, use the 'rand' function to generate a random number between 0 and 1 and divide the range into six equal intervals. Then, determine which interval the random number falls into and return the corresponding integer value (1 to 6). ```MATLAB function result = dice() random_number = rand; if random_number <= 1/6 result = 1; elseif random_number <= 2/6 result = 2; elseif random_number <= 3/6 result = 3; elseif random_number <= 4/6 result = 4; elseif random_number <= 5/6 result = 5; else result = 6; end end ```

Step by step solution

01

Create a MATLAB function

To create the 'dice' function, we will begin by adding the function signature and an end statement: ```MATLAB function result = dice() end ```
02

Generate a random number using 'rand' function

Now, we will generate a random number between 0 and 1 using the 'rand' function: ```MATLAB function result = dice() random_number = rand; end ```
03

Categorize the random number into one of the six intervals

Here, we will divide the range of random values generated by 'rand' into six equal intervals, and determine which interval the generated random number falls into: ```MATLAB function result = dice() random_number = rand; if random_number <= 1/6 result = 1; elseif random_number <= 2/6 result = 2; elseif random_number <= 3/6 result = 3; elseif random_number <= 4/6 result = 4; elseif random_number <= 5/6 result = 5; else result = 6; end end ``` Now, the 'dice' function is complete. Whenever the function is called, it will generate a random number between 0 and 1, classify it into one of the six equal intervals, and return the corresponding integer value (1 to 6), simulating the throw of a fair die.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

MATLAB programming
MATLAB stands out as a highly versatile tool used by engineers, scientists, and students to perform a vast array of computations, from simple arithmetic to complex numerical simulations. It’s designed to make matrix and vector operations straightforward and efficient, as well as providing high-level commands for data analysis, visualization, and developing algorithms.

In the context of our dice simulation exercise, MATLAB programming involves writing a function which is a self-contained block of code that accomplishes a specific task—in this case, simulating the roll of a die. The function is created with inputs and outputs defined, and can be called upon multiple times within a script or command window, which is a fundamental concept of programming to execute repeated tasks efficiently.
Random number generation
Within MATLAB, generating random numbers is a foundational element in simulations and stochastic processes. The 'rand' function is the most straightforward method and returns a pseudo-random number between 0 and 1. These values are uniformly distributed, meaning every number in this range is equally likely to occur.

For our dice simulation, we use this uniform distribution as our basis to simulate each possible outcome of a dice roll, which also has equal likelihood. This core concept is significant in many applications beyond our die-throw simulation, such as Monte Carlo methods, statistical sampling, and random process simulations.
Conditional statements
Conditional statements in MATLAB, using 'if', 'elseif', and 'else', allow for decision-making processes within a function or script. These statements execute code based on the evaluation of one or more conditions; if a condition is true, the corresponding block of code within the statement is executed.

In our die simulation, conditional statements are used to categorize the generated random number into one of six equally likely outcomes. By checking the random number against defined intervals, we simulate the sides (1 through 6) of a fair die. Mastery of conditional statements is crucial for creating interactive and responsive programs.
Function creation
Creating functions in MATLAB is an essential skill for organizing and managing your code. Functions are blocks of code that perform specific tasks and can be reused and called upon. When creating a function, it is given a name (in our case, 'dice'), and can have inputs and outputs. The construction of a function includes the function signature, the body which contains the executable code, and the end statement.

Through function creation in our exercise, we encapsulate the entire process of generating a random number and mapping it to a die's side into a neat, callable structure. This modularity is beneficial for simplifying complex tasks and improving code readability and maintainability.

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Most popular questions from this chapter

Derivative in the Presence of Noise. We will now explore the effects of input noise on the quality of a numerical derivative. First, generate an input vector containing 100 values of the function sinx starting at x=0, using a step size Δx of 0.05, just as you did in the previous problem. Next, use function randomo to generate a small amount of random noise with a maximum amplitude of ±0.02, and add that random noise to the samples in your input vector (see Figure 5.8). Note that the peak amplitude of the noise is only 2% of the peak amplitude of your signal, since the maximum value of sinx is 1. Now take the derivative of the function using the derivative function that you developed in the last problem. How close to the theoretical value of the derivative did you come?

Rayleigh Distribution. The Rayleigh distribution is another random number distribution that appears in many practical problems. A Rayleighdistributed random value can be created by taking the square root of the sum of the squares of two normally distributed random values. In other words, to generate a Rayleigh-distributed random value r get two normally distributed random values (n1 and n2), and perform the following calculation. r=n12+n22 a. Create a function rayleigh (n,m) that returns an nxm array of Rayleigh-distributed random numbers. If only one argument is supplied [rayleigh (n) ], the function should return an n×n array of Rayleigh- distributed random numbers. Be sure to design your function with input argument checking and with proper documentation for the MATLAB help system. b. Test your function by creating an array of 20,000 Rayleigh-distributed random values and plotting a histogram of the distribution. What does the distribution look like? c. Determine the mean and standard deviation of the Rayleigh distribution.

Gravitational Force. The gravitational force F between two bodies of masses m1 and m2 is given by the equation F=Gm1m2r2 where G is the gravitational constant (6.672×1011 N m2/kg2),m1 and m2 are the masses of the bodies in kilograms, and r is the distance between the two bodies. Write a function to calculate the gravitational force between two bodies given their masses and the distance between them. Test your function by determining the force on an 800kg satellite in orbit 38,000 km above the Earth. (The mass of the Earth is 5.98×1024 kg.)

Derivative of a Function. The derivative of a continuous function f(x) is defined by the equation ddxf(x)=limΔx=0f(x+Δx)f(x)Δx In a sampled function, this definition becomes f(xi)=f(xi+1)f(xi)Δx where Δx=xi+1xi Assume that a vector vect contains nsamp samples of a function taken at a spacing of dx per sample. Write a function that will calculate the derivative of this vector from Equation (5.12). The function should check to make sure that dx is greater than zero to prevent divide-by-zero errors in the function. To check your function, you should generate a data set whose derivative is known, and compare the result of the function with the known correct answer. A good choice for a test function is sinx. From elementary calculus, we know that ddx(sinx)cosx. Generate an input vector containing 100 values of the function sinx starting at x=0 and using a step size Δx of 0.05. Take the derivative of the vector with your function, and then compare the resulting answers to the known correct answer. How close did your function come to calculating the correct value for the derivative?

The Birthday Problem. The birthday problem is: if there is a group of n people in a room, what is the probability that two or more of them have the same birthday? It is possible to determine the answer to this question by simulation. Write a function that calculates the probabulity that two or more of n people will have the same birthday, where n is a calling argument. (Hint: To do this, the function should create an array of size n and generate n birthdays in the range 1 to 365 randomly. It should then check to see if any of the n birthdays are identical. The function should perform this experiment at least 5000 times and calculate the fraction of those times in which two or more people had the same birthday.) Write a test program that calculates and prints out the probability that 2 or more of n people will have the same birthday for n=2,3,,40.

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