difference between males and females in sports

difference between males and females in sports

Introduction

This report aims at assessing the difference between males and females in sports. World sports have different sports activities that both the male and female engage in. The various sports ranging from football to athletics. However, some sports are most famous for men than females. Sports, like rugby and football, are being participated by both the female and the male. Other games such as basketball are also being involved by both the male and the female. Many fans follow sports played by men than for the female. For instance, sports like football, famous football players are majorly males. Football players like Lionel Messi and Cristiano Ronaldo are well known by almost every football fan. Very few female football players are well known by football fans. The same applies to rugby and basketball. The above contest brings about the concept of determining the difference between females and males in sports. The research question to be answered is; do females and males differ in games? The data that will be used to answer this question has been obtained from the Kaggle website. The data describes the characteristics of both female and male athletics. Here is the link to the data: https://www.kaggle.com/heesoo37/120-years-of-olympic-history-athletes-and-results. The data majorly focuses on the events, the sports types, and the physical features of the athletics. The above discussion gives us a hint of what to expect from the results. It is expected from the analysis is going to be carried out that we will obtain a significant difference for the male and female in sports. The overshadowed is evident in our day to day sports activities. There is always that variation and deviation of the male and female when it comes to specific activities such as sports.

Background

It is evident that both men and women put in a lot of hard work when it comes to the success of sports. From the beginning, women were treated as the other sex in sports. It was a common belief that sports were meant by the male. The male-dominated different types of games such as rugby and football. The female began to practice different sports in the late ’90s. New games have emerged, and the female has also indulged in those new sports. However, until now, some sports are beloved meant for men. The belief is because the competitions might be very physical, and for this reason, people categorize these sports like men’s kind of sports. Football is a game that demonstrates masculinity, and it is viewed as a sport that requires a lot of physical participation. Therefore, one can state that one of the reasons why women are discriminated in sports is because of their physical capabilities. According to Pfister (2010), bodies and physical differences are the core of sports practices. This determines the rankings and performance of individuals.  The competitive aspects of sports are the very reason why there is scares gender segregation in sports in the 21^st century, especially in the western countries (Senne, 2016; Walker & Bopp, 2011).

Despite the increasing involvement of girls and women in sports, they have been faced with leadership problems. There are underrepresented in leadership position compared to the leadership roles played by men in sports. Women have been given few opportunities in sports leadership, and thus, this has led to a variation of games in men and women (Burton, 2015). This underrepresentation has made it difficult for the female to achieve their goals in sports in the current world. These are a few scenarios where there has been discrimination in sports based on gender.

The above information gives us the go-ahead to determine whether there is a difference between males and females in sports. The research question to be studied is: Is there a difference between make and females in sports. This question can be tackled into different in different angles. The first angle can be the qualitative measures such as leadership and quantitative approaches such as the salary, age, weight, and height. The data to be used present the quantitative measures, and therefore, the quantitative measures will be used to conduct the analysis. The research question will check the difference in male and female athletics in terms of their ages, height, and weight. The analysis will be conducted using the Olympic athletic history data set using statistical software known as SPSS. The results obtained from the SPSS will be used to answer the research question appropriately.

Methods

The data set used was obtained from Kaggle. The data was on the world athlete history. The number of observations in the data was 271116, and the number of variables was 15. The data contained so many missing values. The variables to be used in the research were age, sex, height, and weight. The missing values under these variables were cleaned by dropping the rows that had the missing values. The remaining observations after dropping the rows with the missing values were 206166 rows. The research question will be answered using both descriptive and inferential statistics. The distribution of the height, weight, and age of the athletics will be determined using the histogram. The distribution of the sex will be determined using the bar chart. Later, an ANOVA analysis will be conducted to determine the difference in the athletics ages, weight, and height between the female and the male.

Results

Table 1: Frequency distribution of the gender

Table 1 shows that the total number of both and female and the male was 206165.  Out of the total number of the participants, 67.6 % were male, and 32.4 % were female. This tells us that there were many males who participate in athletics compared to the female.

Fig 1.1: Bar chart of the gender

Fig 1 represents the distribution of gender participation in sports. 67.64 % were male, and 32.36 % were female.

Table 2: Descriptive statistics of age, weight, and height

The table above shows that the median age of the athletes was 24 years. The average age of the athletes was 25.055. The athletes’ age deviated by 5.48 years from the actual mean. The distribution of the age of the athletes was skewed to the right i.e.; skewness value is 1.13. The median height of the athletes was 175 cm. The average height of the athletes was 175.3719. The athletes’ height deviated by 10.546 cm from the actual mean. The distribution of the age of the athletes was normal i.e.; skewness value is 0.0169. The median weight of the athletes was 70 kg. The average weight of the athletes was 70.688 kg — the athletes’ weight deviated by 10.546 cm from the actual mean. The distribution of the weight of the athletes was slightly skewed to the right i.e.; skewness value is 0.79.

Fig 1.2: Histogram of Age

The histogram above shows that the age of the athletes was slightly skewed to the right

Fig 1.3: Histogram of Height

The figure above shows that the distribution of the height was normally distributed

Fig 1.4: Histogram of weight

The histogram above shows that the distribution of the athletes’ height was normally distributed.

ANOVA test

The ANOVA analysis is used to test differences between two and more groups. The hypothesis is formulated before the analysis. The following are the null hypotheses to be tested

Hypothesis testing

H0: The mean age of the male athletes is equal to the mean age of the female athletes

H1: The mean height of the male athletes is equal to the mean height of the female athletes

H2: The mean weight of the male athletes is equal to the mean height of the female athletes

Testing the hypotheses

Table 1.3: Descriptive Statistics

Table 3: ANOVA test

The p-value obtained while testing the mean difference of the ages between the male and female is less than 0.05 i.e., P (0.000 <0.05), therefore, the null hypothesis is rejected, and it is concluded that there is the difference in the mean age of the female and male athletes. The average ages of the males are higher than that of the female. The p-value obtained while testing the difference in height for the male and female was less than 0.05 i.e., P (0.000 <0.05); therefore, the null hypothesis is rejected, and thus, it is concluded that the mean height of the male is higher than that of the female. Similarly, the p-value obtained while testing the difference in weight between the male and the female was less than 0.05 i.e., P (0.000<0.05), therefore, the null hypothesis is rejected and thus, it is concluded that the mean height of the male is higher than that of the following female results obtained from table 3 (Hecke 2012; Moder 2010; Wobbrock et al. 2011; Rojewski, Lee & Gemici, 2012; Abdi & Williams, 2010).

Discussion

The results obtained from the analysis above provide enough evidence that males and females differ in sports. Looking at the age at which the male is participating in sports is different from that of the female. The same applies to the physical features of both the male and female. These are some of the reasons that bring about discrimination in sports. The male can be allowed to participate in sports at a certain age compared to the female.

Conclusion

Following the results obtained from the analysis, we can successfully say that the objective of the research has been achieved. The results have clearly shown that there is a significant difference between males and females in sports. The difference comes in terms of age, weight, and height. However, further research needs to be conducted to test other factors such as salary difference between the male and the female (Harris et al. 2015).

References

Abdi, H., & Williams, L. J. (2010). Tukey’s honestly significant difference (HSD) test. Encyclopedia of Research Design. Thousand Oaks, CA: Sage, 1-5.

Burton, L.J., 2015. Underrepresentation of women in sport leadership: A review of research. Sport management review, 18(2), pp.155-165.

Harris, K. F. H. F., Grappendorf, H., Aicher, T., & Veraldo, C. (2015). “Discrimination? Low pay? Long hours? I am still excited:” Female sport management students’ perceptions of barriers toward a future career in sport. Advancing Women in Leadership, 35, 12-21.

Hecke, T. V. (2012). Power study of anova versus Kruskal-Wallis test. Journal of Statistics and Management Systems, 15(2-3), 241-247.

Moder, K. (2010). Alternatives to F-test in one way ANOVA in case of heterogeneity of variances (a simulation study). Psychological Test and Assessment Modeling, 52(4), 343-353.

Rojewski, J., Lee, I. H., & Gemici, S. (2012). Use of t-test and ANOVA in career-technical education research. Career and Technical Education Research, 37(3), 263-275.

Pfister, G., 2010. Women in sport–gender relations and future perspectives. Sport in Society, 13(2), pp.234-248.

Senne, J. A. (2016). Examination of gender equity and female participation in sport. The Sport Journal, 19, 1-9.

Walker, N. A., & Bopp, T. (2011). The underrepresentation of women in the male-dominated sport workplace: Perspectives of female coaches. Journal of Workplace Rights, 15(1).

Wobbrock, J. O., Findlater, L., Gergle, D., & Higgins, J. J. (2011, May). The aligned rank transform for nonparametric factorial analyses using only anova procedures. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 143-146). ACM.