Pi Day Activities
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Finding Pi Project
Name: ________________________ Finding Pi - Activity Objective: You may already know that pi (π) is a number that is approximately equal to 3.14. But do you know where the number comes from? Let's measure some round objects and find out. Materials: • 6 circular objects Some examples include a bicycle wheel, kiddie pool, trash can lid, DVD, steering wheel, or clock face. Be sure each object you choose is shaped like a perfect circle. • metric tape measure Be sure your tape measure has centimeters on it. • calculator It will save you some time because dividing with decimals can be tricky. • “Finding Pi - Table” worksheet It may be attached to this page, or on the back. What to do: Step 1: Choose one of your circular objects. Write the name of the object on the “Finding Pi” table. Step 2: With the centimeter side of your tape measure, accurately measure the distance around the outside of the circle (the circumference). Record your measurement on the table. Step 3: Next, measure the distance across the middle of the object (the diameter). Record your measurement on the table. Step 4: Use your calculator to divide the circumference by the diameter. Write the answer on the table. If you measured carefully, the answer should be about 3.14, or π. Repeat steps 1 through 4 for each object. Super Teacher Worksheets - www.superteacherworksheets.com Name: ________________________ “Finding Pi” Table Measure circular objects and complete the table below. If your measurements are accurate, you should be able to calculate the number pi (3.14). Is your answer name of circumference diameter circumference ÷ approximately circular object measurement (cm) measurement (cm) diameter equal to π? 1. -
Evaluating Fourier Transforms with MATLAB
ECE 460 – Introduction to Communication Systems MATLAB Tutorial #2 Evaluating Fourier Transforms with MATLAB In class we study the analytic approach for determining the Fourier transform of a continuous time signal. In this tutorial numerical methods are used for finding the Fourier transform of continuous time signals with MATLAB are presented. Using MATLAB to Plot the Fourier Transform of a Time Function The aperiodic pulse shown below: x(t) 1 t -2 2 has a Fourier transform: X ( jf ) = 4sinc(4π f ) This can be found using the Table of Fourier Transforms. We can use MATLAB to plot this transform. MATLAB has a built-in sinc function. However, the definition of the MATLAB sinc function is slightly different than the one used in class and on the Fourier transform table. In MATLAB: sin(π x) sinc(x) = π x Thus, in MATLAB we write the transform, X, using sinc(4f), since the π factor is built in to the function. The following MATLAB commands will plot this Fourier Transform: >> f=-5:.01:5; >> X=4*sinc(4*f); >> plot(f,X) In this case, the Fourier transform is a purely real function. Thus, we can plot it as shown above. In general, Fourier transforms are complex functions and we need to plot the amplitude and phase spectrum separately. This can be done using the following commands: >> plot(f,abs(X)) >> plot(f,angle(X)) Note that the angle is either zero or π. This reflects the positive and negative values of the transform function. Performing the Fourier Integral Numerically For the pulse presented above, the Fourier transform can be found easily using the table. -
William Broadhead Professor of History Thesis Supervisor
Vitruvius on Architecture: A Modem Application and Stability Analysis of Classical Structures by Ana S. Escalante Submitted to the Department of Mechanical Engineering in Partial Fulfillment of the Requirements for the Degree of Bachelor of Science in Mechanical Engineering at the Lj Massachusetts Institute of Technology June 2013 0 2013 Ana S. Escalante. All rights reserved. The author hereby grants to MIT permission to reproduce and to distribute publicly paper and electronic copies of this thesis document in whole or in part in any medium now known or hereafter created Signature of Author: F , 2 I- - Department of Mechanical Engineering May 28, 2013 Certified by: William Broadhead Professor of History Thesis Supervisor Accepted by: Annette Hosoi Professor of Mechanical Engineering Undergraduate Officer 1 2 Vitruvius on Architecture: A Modem Application and Stability Analysis of Classical Structures by Ana S. Escalante Submitted to the Department of Mechanical Engineering on June 7, 2013 in Partial Fulfillment of the Requirements for the Degree of Bachelor of Science in Mechanical Engineering ABSTRACT Imperial Rome has left numerous legacies, the most well-known being its literature and monuments. Though many monuments, such as the Pantheon, are well-preserved, in cases where little physical evidence remains, historians can often use literary sources to inform reconstruction efforts. For more technical studies of Roman construction, technical literature is rare and the contemporary awareness of such literature even less known. When Vitruvius wrote De architectura,he did not intend for it to be a manual for instruction but rather a central source of general architectural knowledge. Directly aimed at architects, contractors, and other individuals involved in the design and construction of buildings, De architecturaprovides insight into contemporary technical knowledge. -
MATLAB Examples Mathematics
MATLAB Examples Mathematics Hans-Petter Halvorsen, M.Sc. Mathematics with MATLAB • MATLAB is a powerful tool for mathematical calculations. • Type “help elfun” (elementary math functions) in the Command window for more information about basic mathematical functions. Mathematics Topics • Basic Math Functions and Expressions � = 3�% + ) �% + �% + �+,(.) • Statistics – mean, median, standard deviation, minimum, maximum and variance • Trigonometric Functions sin() , cos() , tan() • Complex Numbers � = � + �� • Polynomials = =>< � � = �<� + �%� + ⋯ + �=� + �=@< Basic Math Functions Create a function that calculates the following mathematical expression: � = 3�% + ) �% + �% + �+,(.) We will test with different values for � and � We create the function: function z=calcexpression(x,y) z=3*x^2 + sqrt(x^2+y^2)+exp(log(x)); Testing the function gives: >> x=2; >> y=2; >> calcexpression(x,y) ans = 16.8284 Statistics Functions • MATLAB has lots of built-in functions for Statistics • Create a vector with random numbers between 0 and 100. Find the following statistics: mean, median, standard deviation, minimum, maximum and the variance. >> x=rand(100,1)*100; >> mean(x) >> median(x) >> std(x) >> mean(x) >> min(x) >> max(x) >> var(x) Trigonometric functions sin(�) cos(�) tan(�) Trigonometric functions It is quite easy to convert from radians to degrees or from degrees to radians. We have that: 2� ������� = 360 ������� This gives: 180 � ������� = �[�������] M � � �[�������] = �[�������] M 180 → Create two functions that convert from radians to degrees (r2d(x)) and from degrees to radians (d2r(x)) respectively. Test the functions to make sure that they work as expected. The functions are as follows: function d = r2d(r) d=r*180/pi; function r = d2r(d) r=d*pi/180; Testing the functions: >> r2d(2*pi) ans = 360 >> d2r(180) ans = 3.1416 Trigonometric functions Given right triangle: • Create a function that finds the angle A (in degrees) based on input arguments (a,c), (b,c) and (a,b) respectively. -
A Mathematician's Lament
A Mathematician’s Lament by Paul Lockhart musician wakes from a terrible nightmare. In his dream he finds himself in a society where A music education has been made mandatory. “We are helping our students become more competitive in an increasingly sound-filled world.” Educators, school systems, and the state are put in charge of this vital project. Studies are commissioned, committees are formed, and decisions are made— all without the advice or participation of a single working musician or composer. Since musicians are known to set down their ideas in the form of sheet music, these curious black dots and lines must constitute the “language of music.” It is imperative that students become fluent in this language if they are to attain any degree of musical competence; indeed, it would be ludicrous to expect a child to sing a song or play an instrument without having a thorough grounding in music notation and theory. Playing and listening to music, let alone composing an original piece, are considered very advanced topics and are generally put off until college, and more often graduate school. As for the primary and secondary schools, their mission is to train students to use this language— to jiggle symbols around according to a fixed set of rules: “Music class is where we take out our staff paper, our teacher puts some notes on the board, and we copy them or transpose them into a different key. We have to make sure to get the clefs and key signatures right, and our teacher is very picky about making sure we fill in our quarter-notes completely. -
36 Surprising Facts About Pi
36 Surprising Facts About Pi piday.org/pi-facts Pi is the most studied number in mathematics. And that is for a good reason. The number pi is an integral part of many incredible creations including the Pyramids of Giza. Yes, that’s right. Here are 36 facts you will love about pi. 1. The symbol for Pi has been in use for over 250 years. The symbol was introduced by William Jones, an Anglo-Welsh philologist in 1706 and made popular by the mathematician Leonhard Euler. 2. Since the exact value of pi can never be calculated, we can never find the accurate area or circumference of a circle. 3. March 14 or 3/14 is celebrated as pi day because of the first 3.14 are the first digits of pi. Many math nerds around the world love celebrating this infinitely long, never-ending number. 1/8 4. The record for reciting the most number of decimal places of Pi was achieved by Rajveer Meena at VIT University, Vellore, India on 21 March 2015. He was able to recite 70,000 decimal places. To maintain the sanctity of the record, Rajveer wore a blindfold throughout the duration of his recall, which took an astonishing 10 hours! Can’t believe it? Well, here is the evidence: https://twitter.com/GWR/status/973859428880535552 5. If you aren’t a math geek, you would be surprised to know that we can’t find the true value of pi. This is because it is an irrational number. But this makes it an interesting number as mathematicians can express π as sequences and algorithms. -
Double Factorial Binomial Coefficients Mitsuki Hanada Submitted in Partial Fulfillment of the Prerequisite for Honors in The
Double Factorial Binomial Coefficients Mitsuki Hanada Submitted in Partial Fulfillment of the Prerequisite for Honors in the Wellesley College Department of Mathematics under the advisement of Alexander Diesl May 2021 c 2021 Mitsuki Hanada ii Double Factorial Binomial Coefficients Abstract Binomial coefficients are a concept familiar to most mathematics students. In particular, n the binomial coefficient k is most often used when counting the number of ways of choosing k out of n distinct objects. These binomial coefficients are well studied in mathematics due to the many interesting properties they have. For example, they make up the entries of Pascal's Triangle, which has many recursive and combinatorial properties regarding different columns of the triangle. Binomial coefficients are defined using factorials, where n! for n 2 Z>0 is defined to be the product of all the positive integers up to n. One interesting variation of the factorial is the double factorial (n!!), which is defined to be the product of every other positive integer up to n. We can use double factorials in the place of factorials to define double factorial binomial coefficients (DFBCs). Though factorials and double factorials look very similar, when we use double factorials to define binomial coefficients, we lose many important properties that traditional binomial coefficients have. For example, though binomial coefficients are always defined to be integers, we can easily determine that this is not the case for DFBCs. In this thesis, we will discuss the different forms that these coefficients can take. We will also focus on different properties that binomial coefficients have, such as the Chu-Vandermonde Identity and the recursive relation illustrated by Pascal's Triangle, and determine whether there exists analogous results for DFBCs. -
Numerous Proofs of Ζ(2) = 6
π2 Numerous Proofs of ζ(2) = 6 Brendan W. Sullivan April 15, 2013 Abstract In this talk, we will investigate how the late, great Leonhard Euler P1 2 2 originally proved the identity ζ(2) = n=1 1=n = π =6 way back in 1735. This will briefly lead us astray into the bewildering forest of com- plex analysis where we will point to some important theorems and lemmas whose proofs are, alas, too far off the beaten path. On our journey out of said forest, we will visit the temple of the Riemann zeta function and marvel at its significance in number theory and its relation to the prob- lem at hand, and we will bow to the uber-famously-unsolved Riemann hypothesis. From there, we will travel far and wide through the kingdom of analysis, whizzing through a number N of proofs of the same original fact in this talk's title, where N is not to exceed 5 but is no less than 3. Nothing beyond a familiarity with standard calculus and the notion of imaginary numbers will be presumed. Note: These were notes I typed up for myself to give this seminar talk. I only got through a portion of the material written down here in the actual presentation, so I figured I'd just share my notes and let you read through them. Many of these proofs were discovered in a survey article by Robin Chapman (linked below). I chose particular ones to work through based on the intended audience; I also added a section about justifying the sin(x) \factoring" as an infinite product (a fact upon which two of Euler's proofs depend) and one about the Riemann Zeta function and its use in number theory. -
Pi, Fourier Transform and Ludolph Van Ceulen
3rd TEMPUS-INTCOM Symposium, September 9-14, 2000, Veszprém, Hungary. 1 PI, FOURIER TRANSFORM AND LUDOLPH VAN CEULEN M.Vajta Department of Mathematical Sciences University of Twente P.O.Box 217, 7500 AE Enschede The Netherlands e-mail: [email protected] ABSTRACT The paper describes an interesting (and unexpected) application of the Fast Fourier transform in number theory. Calculating more and more decimals of p (first by hand and then from the mid-20th century, by digital computers) not only fascinated mathematicians from ancient times but kept them busy as well. They invented and applied hundreds of methods in the process but the known number of decimals remained only a couple of hundred as of the late 19th century. All that changed with the advent of the digital computers. And although digital computers made possible to calculate thousands of decimals, the underlying methods hardly changed and their convergence remained slow (linear). Until the 1970's. Then, in 1976, an innovative quadratic convergent formula (based on the method of algebraic-geometric mean) for the calculation of p was published independently by Brent [10] and Salamin [14]. After their breakthrough, the Borwein brothers soon developed cubically and quartically convergent algorithms [8,9]. In spite of the incredible fast convergence of these algorithms, it was the application of the Fast Fourier transform (for multiplication) which enhanced their efficiency and reduced computer time [2,12,15]. The author would like to dedicate this paper to the memory of Ludolph van Ceulen (1540-1610), who spent almost his whole life to calculate the first 35 decimals of p. -
An Introduction to the Mandelbrot Set
An introduction to the Mandelbrot set Bastian Fredriksson January 2015 1 Purpose and content The purpose of this paper is to introduce the reader to the very useful subject of fractals. We will focus on the Mandelbrot set and the related Julia sets. I will show some ways of visualising these sets and how to make a program that renders them. Finally, I will explain a key exchange algorithm based on what we have learnt. 2 Introduction The Mandelbrot set and the Julia sets are sets of points in the complex plane. Julia sets were first studied by the French mathematicians Pierre Fatou and Gaston Julia in the early 20th century. However, at this point in time there were no computers, and this made it practically impossible to study the structure of the set more closely, since large amount of computational power was needed. Their discoveries was left in the dark until 1961, when a Jewish-Polish math- ematician named Benoit Mandelbrot began his research at IBM. His task was to reduce the white noise that disturbed the transmission on telephony lines [3]. It seemed like the noise came in bursts, sometimes there were a lot of distur- bance, and sometimes there was no disturbance at all. Also, if you examined a period of time with a lot of noise-problems, you could still find periods without noise [4]. Could it be possible to come up with a model that explains when there is noise or not? Mandelbrot took a quite radical approach to the problem at hand, and chose to visualise the data. -
Does Mathematical Beauty Pose Problems for Naturalism?1
Does Mathematical Beauty Pose Problems for Naturalism?1 Russell W. Howell Professor of Mathematics Westmont College, Santa Barbara, CA [email protected] Numerous events occurred in 1960 whose eects could hardly have been predicted at the time: several African Americans staged a sit-in at a Greensboro lunch counter, the Soviet Union shot down Gary Powers while he was ying a U2 spy plane, the US FDA approved the use of the rst oral contraceptive, AT&T led with the Federal Communications Commission for permission to launch an experimental communications satellite, and four Presidential debates between John Kennedy and Richard Nixon aired on national television. Less well known was the publication of a paper by the physicist Eugene Wigner. Ap- pearing in Communications in Pure and Applied Mathematics, a journal certainly not widely read by the general public, it bore the mysterious title The Unreasonable Eectiveness of Mathematics in the Natural Sciences. (Wigner, 1960) Like our cultural examples of the 1960's, it has had eects beyond what most people would have imagined. Our purpose here is to tease out some strains of an important question that has emerged from Wigner's work. Wigner begins with a story about two friends who were discussing their jobs. One of them, a statistician, was working on population trends. He mentioned a paper he had produced, which contained the Gaussian distribution equation near the beginning. The statistician attempted to explain the meaning it, as well as other mathematical symbols. His friend was a bit perplexed, and was not quite sure whether the statistician was pulling his leg. -
Bridge Design Manual (BDM), 2006
Bridge Design Manual June 2006 WWW.SCDOT.ORG Welcome To The SCDOT Bridge Design Manual Chapter 1 – Bridge Design Section Organization Chapter 2 – Bridge Replacement Project Development Chapter 3 – Procedures for Plan Preparation Chapter 4 – Coordination of Bridge Replacement Projects Chapter 5 – Administrative Policies and Procedures Chapter 6 – Plan Preparation Chapter 7 – Quantity Estimates Chapter 8 – Construction Cost Estimates Chapter 9 – Bid Documents Chapter 10 – [Reserved] Chapter 11 – General Requirements Chapter 12 – Structural Systems and Dimensions Chapter 13 – Loads and Load Factors Chapter 14 – Structural Analysis and Evaluation Chapter 15 – Structural Concrete Chapter 16 – Structural Steel Structures Chapter 17 – Bridge Decks Chapter 18 – Bridge Deck Drainage Chapter 19 – Foundations Chapter 20 – Substructures Chapter 21 – Joints and Bearings Chapter 22 – Highway Bridges Over Railroads Chapter 23 – Bridge Widening and Rehabilitation Chapter 24 – Construction Operations Chapter 25 – Computer Programs Chapter 1 BRIDGE DESIGN SECTION ORGANIZATION SCDOT BRIDGE DESIGN MANUAL April 2006 SCDOT Bridge Design Manual BRIDGE DESIGN SECTION ORGANIZATION Table of Contents Section Page 1.1 BRIDGE DESIGN SECTION...................................................................................1-1 1.1.1 State Bridge Design Engineer..................................................................1-1 1.1.2 Seismic Design and Bridge Design Support Team..................................1-2 1.1.3 Bridge Design Teams...............................................................................1-3