Abstract
The focus of this laboratory experiment was to determine whether or not sports ability was decreased for those born in summer months. The participants were provided with a questionnaire and the data was analyzed through Excel using a Chi Square test of association. It was found that the null hypothesis, stating that there is no greater than expected participation, could not be rejected through the results.

You're lucky! Use promo "samples20"
and get a custom paper on
"Summer Born Children and Sporting Ability"
with 20% discount!
Order Now

Introduction
Research suggests that children within a particular year have varying sports abilities based on their age. That is, those younger children have less sports abilities than older children in the same year (Sykes, Bell, & Rodeiro, 2009). This phenomenon is known as the ‘birth date effect’ and those children with summer birthdays (i.e.: June, July, and August) have the greatest disadvantages in relation to sports abilities (Sykes, Bell, & Rodeiro, 2009). It has been seen that this phenomenon develops regardless of where the student is located. For example, UK student intakes begin on September 1st. This means that those born in September, October, or November have advantages in relation to sporting abilities. On the other hand, other countries that have a student intake that begins on January 1st would see advantages for those born in January, February, or March. At the same time, disadvantages would be seen in those born in October, November, or December (Sykes, Bell, & Rodeiro, 2009). The purpose of this laboratory is to determine how accurate the birth date effect is in relation to summer born students on sports ability.

Method
Through the completion of the laboratory experiment, the research question answered was: Will we find evidence of birth date effects in sports participation during secondary school (11-18) in a sample of University students? It is hypothesized that there is a significant association between time of year birth date and sporting activity. Furthermore, it is hypothesized that there is a greater than expected involvement in sports participation for those students born during the autumn and winter months. At the same time, the null hypothesis is that there is not a greater than expected involvement in sports participation for those students born during the autumn and winter months. The laboratory will be conducted through a questionnaire provided to participants, which is then used to conduct a statistical analysis. The statistical analysis is divided into two parts. The first portion of the statistical analysis involves determining if there is a significant association between birth dates and sportiness using birth dates split into two. The second portion of the statistical analysis only uses the oldest quarter of students and youngest quarter of students within the given year.

Participants
In order to be selected for participation in the laboratory experiment, students needed to be University students that participated in sports during secondary school. However, data inclusion was dependent on when the participant had school intake. In this case, the school intake was September 1st. Because of this requirement, 32 participants were not included into the analysis because the school start date was a date other than September 1st. The specific analysis method used is the Chi Square test.

Apparatus
For this study, the apparatus used is a questionnaire in order to collect data from the participants. The questions asked were: (1) Was the intake of your primary school on the 1st of September?; (2) How many hours per week did you participate in voluntary sporting activity during your time at secondary school?: (3) Did you represent your school, or other, in any sport when at secondary school; and (4) In which quarter of the year is your birthday? As noted previously, data analysis will occur through a two-part statistical Chi Square test analysis.

Procedure
Based on the questions asked in the questionnaire, the independent variable is time of year of birth (asked in question 4) and the dependent variables are hours spent in playing voluntary sports at secondary school (asked in question 2) and whether sports participation was done to represent the school or other organization (asked in question 3). The first Chi Square test is designed to be a 2×2 Chi Square test of association in order to answer the research question. This is done by creating two distinct categories for each individual test. The independent variable involves categories of dividing birth dates into autumn/winter (category 1) and spring/summer (category 2). The first dependent variable (hours spent) involves dividing the hours spent into high and low categories. The second dependent variable (sports representation) involves dividing the sports representation into yes and no categories. The results of the questionnaire are entered into Excel for division purposes, then analyzed to create frequency counts for the 2×2 Chi Square test of association.

Discussion
Background research shows that the birth date effect is more predominant during infancy and primary years. However, the effect decreases as the child ages. At the same time, there is a 6% lower attainment level for those students born during the summer than during autumn (Bell, Massey, & Dextor, 1997). The variables for this study were concluded to be the pre-stated independent variable is birth date, whereas the dependent variable is sports representation. This is because the other dependent variable (hours spent participating in sports) created a variation of results that were too widely varied. For example, low values were considered to be under 3 and the remaining values were considered to be high. This was deemed to be too variate because some students reported sports participation of 20+ hours per week. The first Chi Square test yielded a result of 0.887. At the same time, the second Chi Square test yielded a result of 0.002. With a probability of 0.95, the critical value was 3.84. Both Chi Squares were below this critical value. Therefore, the null hypothesis cannot be rejected. This means that it is entirely possible that sports participation is greater than average for those born in the autumn/winter months.

    References
  • Bell, J. F., Massey, A., & Dexter, T. (1997). Birth date and ratings of sporting achievement: analysis of physical education GCSE results. European journal of physical education, 2(2), 160-166.
  • Sykes, E. D., Bell, J. F., & Rodeiro, C. V. (2009). Birth date Effects: A Review of the Literature from 1990-on. Unpublished paper, University of Cambridge.