Math Studies Sl Internal Assessment

Topics: Gender, Male, Female Pages: 10 (2300 words) Published: March 20, 2013
Dependency of a Boxer’s Win rate on Reach and Gender
Antonio Paolo Gomez
Candidate No. 003902-006
Northbridge International School Cambodia
Math Studies Internal Assessment
Word Count: 1655

Statement of Task3
Math Processes5
Simple math processes:5
Pearson’s Correlation Coefficient r:7
Works Cited11

Statement of Task
Boxing is a very well known sport around the world, where two disciplined athletes face off in a ring, trading blows until one of them submits or until judges decide a winner. The sport revolves around throwing blows with their fists, and to organize said athletes, their characteristics are measured, and their accomplishments are recorded. Before a fight is held, a fighter’s profile is summarized, mentioning the person’s height, weight, reach, and their win/loss record. All of what is mentioned is said to play a big part in the flow of the match. The purpose of this investigation is to determine if there is a relationship between a boxer’s reach and his winning rate. The data that will be taken will be professional boxers’ measured reach and their counts of wins and losses for winning rate. The measurement of a boxer’s reach is used to determine how far he can extend his punch. The measure of boxers’ reaches and their records of wins and losses will be used to determine if reach is one of the larger factors that affect an athlete’s chances in a match. Plan

The investigation will include data gathered from professional boxers, which are their reach and their counts of wins and losses. The data that will be collected can be collected from official sites online, which have brief profiles of athletes’ measurements. I will be using official sites since they tend to be up to date and have accurate and legit information. The amount of data collected will consist of 30 athletes, half of whom are male and half are female. The data will be collected from official boxing sites such as, which contains the profiles of numerous official boxers and their measurements, which includes their reach and wins and losses. The data for one athlete will consist of his reach and his win/loss record. I will attempt to avoid any professional athletes that are relatively new to the professional stage, so I will be looking at boxers with around at least five years of experience. Once the data has been acquired, the data will be analyzed using different mathematical processes. A scatter plot will be used to plot out said data. The correlation coefficient r will be calculated. The  test of independence will be used to determine if there is a dependency between a boxer’s gender and winning rate. Data

| Males| |
Boxer| Reach (cm)| Win Rate (%)|
1| 170| 90.00|
2| 173| 96.77|
3| 183| 96.88|
4| 194| 88.57|
5| 183| 87.88|
6| 207| 92.31|
7| 177| 94.29|
8| 183| 72.34|
9| 201| 100.00|
10| 198| 95.24|
11| 198| 80.77|
12| 179| 86.21|
13| 179| 89.29|
14| 183| 87.88|
15| 180| 89.66|
| Females| |
Boxer| Reach (cm)| Win Rate (%)|
1| 165| 89.47|
2| 161| 86.67|
3| 167| 66.04|
4| 166| 75.00|
5| 162| 81.25|
6| 168| 93.33|
7| 163| 76.47|
8| 162| 75.00|
9| 159| 88.46|
10| 167| 86.21|
11| 176| 80.95|
12| 171| 83.87|
13| 168| 82.61|
14| 166| 78.95|
15| 169| 90.48|

From the scatter plot using both male and female sets of data, we can predict that the calculated correlation would be weak and that a boxer’s win rate weakly correlates with his/her reach. This can be seen as the data points are spread and plotted quite far from the line of best fit.

Math Processes

Simple math processes:
Average: Males
* Reach in centimeters:
170+173+183+194+183+207+177+183+201+198+198+179+179+183+180=2788 2788/15= 185.8666667 cm...
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