MATH 125 UW Finite Mathematics & Modeling Statistics & the Olympic Games Project
Finite Mathematics & Modeling (MATH 125) is a general education course designed to assist students in the development of critical life skills. One of the goals of this assignment is to assess students’ competence for each of these objectives: Written and Oral Communication Skills – examine the mathematical contributions made by people from diverse cultures throughout history, and their social, and cultural significance (CCO 14),Critical Analysis and Reasoning – evaluate cultural and social applications and approaches to statistical analysis (CCO16),Information Literacy – find, evaluate, use, and cite academic resources for conducting research in mathematics (CCO17),Scientific and Quantitative or Logical Reasoning – describe, numerically and graphically, various forms and presentations of statistical data (CCO13).Descriptive statisticsStatistical displays of dataAnalyzing and interpreting statistics in a global community III.Technological Competence – apply technology to the solution of mathematical problems (CCO9), In addition to the above general education objectives, this assignment assesses students’ understanding and application of the following skills and knowledge specific to Finite Mathematics & Modeling (MATH 125). Elementary Statistics: ASSIGNMENT: Purpose: The purpose of this assignment is to provide you with an opportunity to demonstrate the ability to analyze and compare two sets of data using the statistical methods discussed in this course. Audience: The audience for your report will be your instructor. In general, assume the person reading your report has little background knowledge of historical racing times, but enough background knowledge in statistics to be able to understand your analysis. Directions: Please respond to all questions using complete sentences, linking your mathematical statements with proper exposition. Be sure to satisfy the length requirement for questions that indicate one. ASSIGNMENT SPECIFICATIONS: This assignment is to be completed individually as a take-home project. The length of your report should be adequate to have fully answered each question.Your project should be typed; however, mathematical calculations may be handwritten.Your facts must be properly cited with in-text parenthetical citations and a Works Cited page.http://owl.english.purdue.edu/owl/resource/747/01/http://www.ccbcmd.edu/Resources-for-Students/Tutoring-and-Academic- Coaching/Writing-Center- and-Online-Writing-Lab/Documenting-and-Citing-Sources.aspxThis assignment will account for at least 10% of your total course grade.See attached rubric for details about how your project will be graded. This project is due on In Fall 2020 this date should not be before November 16.For paper submissions, please submit TWO copies. One copy should include your student ID, course number and section and omit student and faculty names. The other will be evaluated within your course and should include the student name.Electronic submissions should be made with the student’s ID number (900 or 901#) as the file name through Blackboard. Student and instructor names should not appear on electronic submissions. For citation, use the Modern Language Association (MLA) format and use parenthetical citation with a Works Cited list as the final page (non-content page). Purdue University offers a very good online reference at their Writing Lab's website. GRADING: SUBMISSION GUIDELINES: Statistics & the Olympic Games The 10,000 meters is a standard track event and it is a part of both the Olympic Games and World Championships. A sample from the top 17 finishers of the men’s and women’s races from the 2015 World Championships are listed in the attached data tables. Calculate the mean, median, range, and standard deviation for each data set.Suppose the timing device used in the men’s race failed to activate at the start of the race and instead began to record the times x seconds into the race.Determine who placed 20thin the men’s and in the women’s 10,000 meter races at the 2016 Summer Olympics in Rio de Janeiro.If both of those 20thplace finishers from question #3, had competed in the 2015 World Championships with their 2016 Olympic time, where would they have placed?The calculation for standard deviation is accredited to Francis Galton. In three to five sentences, describe the life of Francis Galton and specifically why he may have needed a calculation for the standard deviation or variance. You are expected to use at least two (2) technology tools to make your calculations (such as a calculator, Microsoft Excel, etc.). State specifically what technology you used. If you choose to use Microsoft Excel, instructions for these calculations can be found here: http://researchbasics.education.uconn.edu/calculatingmeanstandarddev Consider how the competitors’ times would be affected. Would the x seconds be added to or subtracted from the times recorded to find the true times? Would the median you calculated in question #1 be affected? If yes, how?If no, why not? Record the names, nationalities, and times. Be sure to properly cite at least two (2) sources on a Works Cited page. Under Assignment Specifications below, there are some guidelines to help you with citing your sources. Which one would have done relatively better than the other at the 2015 World Championships? Justify your answer mathematically. Consider using more than one method to justify your answer. For assistance converting minutes into seconds, view this video: https://www.khanacademy.org/math/4th-engage-ny/engage-4th-module-7/4th-module-7- topic- a/v/time-unit-conversion Men’s 2015 World Championship – Final Results (top 17 finishers) Rank Name Nationality Time (seconds) 1 Mo Farah Great Britain (GBR) 1621.13 2 Geoffrey Kipsang Kenya (KEN) 1621.76 3 Paul Tanui Kenya (KEN) 1622.83 4 Bedan Karoki Kenya (KEN) 1624.77 5 Galen Rupp United States (USA) 1628.91 6 Abrar Osman Eritrea (ERI) 1663.21 7 Ali Kaya Turkey (TUR) 1663.69 8 Timothy Toroitich Uganda (UGA) 1664.90 9 Joshua Kiprui Cheptegei Uganda (UGA) 1668.89 10 Muktar Edris Ethiopia (ETH) 1674.47 11 Mosinet Geremew Ethiopia (ETH) 1687.50 12 El Hassan El-Abbassi Bahrain (BHR) 1692.57 13 Nguse Tesfaldet Eritrea (ERI) 1694.72 14 Cameron Levins Canada (CAN) 1695.19 15 Hassan Mead United States (USA) 1696.30 16 Shadrack Kipchirchir United States (USA) 1696.30 17 Arne Gabius Germany (GER) 1704.47 Women’s 2015 World Championship – Final Results (top 17 finishers) Rank Name Nationality Time (seconds) 1 Vivian Cheruiyot Kenya (KEN) 1901.31 2 Gelete Burka Ethiopia (ETH) 1901.77 3 Emily Infeld United States (USA) 1903.49 4 Molly Huddle United States (USA) 1903.58 5 Sally Kipyego Kenya (KEN) 1904.42 6 Shalane Flanagan United States (USA) 1906.23 7 Alemitu Heroye Ethiopia (ETH) 1909.73 8 Betsy Saina Kenya (KEN) 1911.35 9 Belaynesh Oljira Ethiopia (ETH) 1913.01 10 Susan Kuijken Netherlands (NED) 1914.32 11 Jip Vastenburg Netherlands (NED) 1923.03 12 Sara Moreira Portugal (POR) 1926.14 13 Kasumi Nishihara Japan (JPN) 1932.95 14 Brenda Flores Mexico (MEX) 1935.26 15 Kate Avery Great Britain (GBR) 1936.19 16 Trihas Gebre Spain (ESP) 1940.87 17 Juliet Chekwel Uganda (UGA) 1940.95 International Association of Athletics Federations. 15th IAAF World Championships Timetable by Discipline, www.iaaf.org/competitions/iaaf-world-championships/15th-iaaf-world-championships- 4875/timetable/by discipline. Accessed 5 Oct. 2016.