Math Studies Sl Internal Assessment Boxing Essay Example

boxing sites such as BoxRec. com, 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. 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
• Win rate in percentage: 90. 00+96. 77+96. 88+88. 57+87. 88+92. 31+94. 29+72. 34+100+95. 24+80. 77+86. 21+89. 29+87. 88+89. 66= 1348. 09 1348. 09/15= 89. 87% Average: Females
• Reach in centimeters: 165+161+167+166+162+168+163+162+159+167+176+171+168+166+169= 2490 2490/15= 166 cm
• Win rate in percentage: 89. 7+86. 67+66. 04+75+81. 25+93. 33+76. 47+75+88. 46+86. 21+80. 95+83. 87+82. 61+78. 95+90. 48=1234. 76 1234. 76/15=82. 32 Average: both genders
• Reach in centimeters: 2788+2490=5278 5278/30=175. 93 cm
• Win
  

rate in percentage: 1348. 09+1234. 76= 2582. 85 2582. 85/30= 86. 095%

We can see a small difference in win rate between the genders, with male boxers having a higher win rate by about 7%. We can see a bigger difference between the reach of the two genders but this would most likely be because men tend to grow and develop their bodies naturally larger than women.

We are able to see that the standard deviation is greater for the male boxers female boxers. We can assume that the pieces of data from the men are spread farther from the mean as compared to the data from the women. This means that in regards to the data collected, female boxers seem to be closer n their measured reach as compared to the males. The standard deviation for both groups surpasses the calculated standard deviation for the separate male and female groups, meaning that as a whole range of data, the reaches recorded altogether are even more spread out from the average as compared to the genders separately.

Standard Deviation

Win rate:

Males: Sx=90-89. 872+96. 77-89. 872+96. 88-89. 872+88. 57-89. 872…89. 66-89. 87215 Sx=6. 67

Females: Sx=89. 47-82. 322+86. 67-82. 322+66. 04-82. 322+75-82. 322…90. 48-82. 32215 Sx=6. 995

Both Genders: Sy=90. 00-86. 0952+96. 7-86. 0952+96. 88-86. 0952+88. 57-86. 0952…90. 48-86. 095230 Sy = 7. 8087

We can see from the calculated standard deviations that the standard deviation for the win rate of males and females are close to each other, meaning that both have pieces of data that are similarly far from the calculated mean. In regards to

all data recorded regardless of gender, the standard deviation is found to be slightly higher, meaning that the pieces of data for both genders are slightly farther from the mean as compared to the separate gender groups of data.

Correlation coefficient r is calculated to be very weak, meaning that reach and win rate show very little correlation and that a boxer’s reach is not a big factor of his or her chances of victory. With low correlation between a boxer’s reach and win rate, I will now see if gender is a factor of an athlete’s win rate by calculating chi squared.

Degrees of freedom= 1 Significance level= 5% 5% significance is used because it is the most common level of significance used. HO= Gender and win rate are independent of each other H1= Gender and win rate are dependent on each other. The 2 critical value at 5% significance with 1 degrees freedom is found to be 3. 841. The 2 value is greater than the critical value: 7. 33>3. 841, the null hypothesis is rejected and it can therefore be assumed that a boxer’s win rate is dependent on his or her gender.

Discussion/Validity

The investigation carried out to observe the correlation of Win rate and reach and win rate and gender has a few limitations that have affected the outcome of the results. One limitation is that although it is taken into account the reach of each boxer, their size and weight places them in different classes for professional fights. This means that fighters would normally be fighting people that have similar size, and theoretically, similar reach.