ASSIGNMENT: In this assignment, students will evaluate data from the 10,000 meter race of the 2019 World Championships. Students will calculate descriptive statistics, evaluate possible implications for faulty timing equipment, and compute relative placements for 2020 Olympic runners. Additionally, students will logically apply statistical reasoning to discuss code breaking strategies.

• Your project should be typed; however, mathematical calculations may be submitted as a photo within the document.
• Your facts must be properly cited with in-text parenthetical citations and a Works Cited page.

For citation, use the Modern Language Association format and use parenthetical citation with a Works Cited list as the final page (non-content page).

• http://www.ccbcmd.edu/Resources-for-Students/Tutoring-and-Academic- Coaching/Writing-Center- and-Online-Writing-Lab/Documenting-and-Citing-Sources.aspx
• http://owl.english.purdue.edu/owl/resource/747/01/

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 2019 World Championships are listed in the attached data tables.

1. Calculate the mean, median, range, and standard deviation foreach data set.

• 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

1. 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 timesxseconds into the race.

• Consider how the competitors' times would be affected.
• Would thexseconds 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?

1. Determine who placed 9^th in the men's and in the women's 10,000 meter races at the 2020 Summer Olympics (which occurred in 2021) in Tokyo.

• Record the names, nationalities, and times.
• Be sure to properly cite at least two (2) sources on a Works Cited page.
• UnderAssignment Specificationsbelow, there are some guidelines to help you with citing your sources.

1. If both of those 9^th place finishers from question #3, had they competed in the 2019 World Championships with their 2020 Olympic time (which occurred in 2021), where would they have placed?

• Which one would have done relatively better than the other at the 2019 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

5. One of the first recorded uses of statistics was in the 9th century by an Arab Muslim philosopher, Al-Kindi. He was studying cryptanalysis, or codebreaking, and realized that the most frequently occurring letters in a cypher should correspond to the most frequently occurring letters in the alphabet.

Inthree to five sentences, with source(s) cited, determine and explain what the most frequently occurring letters are in the English alphabet (and what their frequencies are). Once you have that, use that information to explain how you would use it to try to break this code (you do not have to actually break it, but you can if you want).

Men's 2019 World Championship - Final Results (top 17 finishers)

Rank	Name	Nationality	Time (seconds)
1	Joshua Cheptegei	Uganda (UGA)	1608.36
2	Yomif Kejelcha	Ethiopia (ETH)	1609.34
3	Rhonex Kipruto	Kenya (KEN)	1610.32
4	Rodgers Kwemoi	Kenya (KEN)	1615.36
5	Andamlak Belihu	Ethiopia (ETH)	1616.71
6	Mohammed Ahmed	Canada (CAN)	1619.35
7	Lopez Lomong	United States (USA)	1624.72
8	Yemaneberhan Crippa	Italy (ITA)	1630.76
9	Hagos Gebrhiwet	Ethiopia (ETH)	1631.37
10	Shadrack Kipchirchir	United States (USA)	1644.74
11	Sondre Nordstad Moen	Norway (NOR)	1682.18
12	Leonard Korir	United States (USA)	1685.73
13	Soufiane Bouchikhi	Belgium (BEL)	1695.43
14	Aron Kifle	Eritrea (ERI)	1696.74
15	Rodrigue Kwizera	Burundi (BDI)	1701.92
16	Abdallah Kibet Mande	Uganda (UGA)	1710.49
17	Onesphore Nzikwinkunda	Burundi (BDI)	1751.50

Women's 2019 World Championship - Final Results (top 17 finishers)

Rank	Name	Nationality	Time (seconds)
1	Sifan Hassan	Netherlands (NED)	1817.62
2	Letesenbet Gidey	Ethiopia (ETH)	1821.23
3	Agnes Jebet Tirop	Kenya (KEN)	1825.20
4	Rosemary Monica Wanjiru	Kenya (KEN)	1835.75
5	Hellen Obiri	Kenya (KEN)	1835.82
6	Senbere Teferi	Ethiopia (ETH)	1844.23
7	Susan Krumins	Netherlands (NED)	1865.40
8	Marielle Hall	United States (USA)	1865.71
9	Molly Huddle	United States (USA)	1867.24
10	Emily Sisson	United States (USA)	1872.56
11	Hitomi Niiya	Japan (JPN)	1872.99
12	Camille Buscomb	New Zealand (NZL)	1873.21
13	Ellie Pashley	Australia (AUS)	1878.89
14	Sinead Diver	Australia (AUS)	1885.49
15	Stephanie Twell	Great Britain (GBR)	1904.79
16	Stella Chesang	Uganda (UGA)	1935.20
17	Natasha Wodak	Canada (CAN)	1951.19