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Unit 5 Research Project
Worthing College Sports Science
[Rob Fogerty ]
2015
Investigate the relationship between
height and PB performance of 100m
sprinters who competed in London
2012?
P2: Carry out / P4: Produce
Abstract
Write your own abstract for your research project here. Use the experience from the literacy
review task as the basis for writing your own abstract. This should be the last part of the write-up
that you complete.
The aim of the study was to investigate the relationship between height and PB performance of
100m sprinters who competed in London 2012? A sample of 73 elite male sprinters who
competed in London 2012 were all analysed in terms of there heights and there personal best
times the study compared to set variables height and personal best performance. The data was
collected by using the IAAF and London 2012 website as well as other secondary sources for
those athletes who’s data was difficult to collect. Using the data that had been collected , the
elite sprinters heights and personal bests were all entered into Microsoft excel and the data was
then used to produce a scatter graph to see if a correlation existed, initially results from the
scatter graph started to indicate that taller athletes in fact had better personal bests but the data
was not significant, further investigation Using spearman's rank correlation coefficient showed
the level of correlation was 0.582716 concluding that there was no significant relationship
between height and personal best performance.
P2: Carry out / P4: Produce
Contents: General
In this section you need to write a page by page contents page (correctly numbered for pages 3-26)
Slide 3 – Abstract
Slide 4 –
Slide 4general
Slide 5 – appendices
Slide 6- figures and tables
Slide 7– acknowledgements
Slide 8 – introduction
Slide 9 - literature review and references
Slide 10 – project hypothesis
Slide 11 – method
Slide 12 – data collection
Slide 13 – data analysis
Slide 14– results
Slide 15– discussion
Slide 16 conclusion
Slide17– review 1/3
Slide 18– review 2/3
Slide 19 – review 3/3
Slide 20 – future recommendations 1/5
Slide 21 – future recommendation 2/5
Slide 22- future recommendation 3/5
Slide 23- future recommendation 4/5
Slide 24- future recommendation 5/5
Slide 25-research project appendices
Slide 26- Appendix 1
P2: Carry out / P4: Produce
Contents: Appendices
In this section you need to write a page by page contents page (correctly numbered for pages 27-32)
Page 27- Appendix 2.
Page 28-Research project figures and tables.
Page 29- Figures and tables 1.
Page 30-Figures and tables 2.
Page 31-Figures and tables 3.
Page 32- Figures and tables 4.
P2: Carry out / P4: Produce
Contents: Figures and Tables
P2: Carry out / P4: Produce
Page 31- Figures and tables 1 screenshot of spearman correlation coefficient
for my individual research as well as Spearman’s ranking scale.
Page 32- Figures and table 2. screenshot of my sample size on Microsoft
excel showing the sample size of my participants involved within the
research.
Page 33- Figures and tables 3. Screenshot of my scatter graph representing
to variables within my sample size showing height in correlation to personal
best time.
Page 34- Figures and tables 4. screenshot showing the central tendency
within my sample eg mean, median, mode.
Acknowledgements
On this page you need to thank everyone who contributed to making your project a
success. Think about the subjects, classmates and others that have helped you and
how they helped you.
Without the secondary information I gathered from the IAAF, London 2012 Olympics
website and other secondary sources I would not have been able to carry out my
research project.
Without the help and guidance from Andy Strickland in my research project in terms
of data analysis I would not have been able to get a clear distinction between my two
variables.
P2: Carry out / P4: Produce
Introduction
Here you need to introduce your project.
What is the aim? To investigate the relationship between height and PB
performance of 100m athletes who competed in London 2012.
Why did you choose the aim?
I chose this aim because I have a keen interest into elite sprinting it has
always fascinated me as to the mechanics of what makes an elite sprinter and
whether a elite sprinter has been nurtured or nature. I also chose this aim
because I felt that this field or research had a lot of potential and I could draw
out many different topics with my conclusions after I had conducted my
research.
What was the project timescale? 2 months.
P2: Carry out / P4: Produce
Literature Review and References
Add a hyperlink to your WordPress literacy review here.
http://alturl.com/x4qq3
P2: Carry out / P4: Produce
Project Hypothesis
What is your project hypothesis (or hypotheses)?
I expect to find that in fact that height does have an affect on PB performance in 100m
athletes who competed in London 2012.
I expect to find that there are many other factors that contribute to PB performance in
100m athletes who competed in London 2012.
Remember your hypothesis is an educated guess about how things work and what you
expect to find. Your hypothesis should be what you test in your project and is
therefore a testable hypothesis.
A hypothesis is often written like: "If _____[I do this] _____, then _____[this]_____
will happen."
P2: Carry out / P4: Produce
Method
Use your unit 4 work to help you write your detailed method. A useful reminder of the Unit 4 content is
linked on page 2 here.
Your method should include detailed instructions. What you are going to do, how are you going to do it,
who is going to do it and when key actions will be completed.
You should add relevant diagrams for any testing you do In the research project figures and tables
section.
26
At the start of my research project I initially had to identify the athletes who were involved in the
London 2012 100m qualifying rounds, to do this I had to go on the London 2012 website and gather the
information of the athletes name and the sample size involved. After gathering the information I then
had to identify the 74 athletes individuals heights and weights, to do this I typed in on google search
engine IAAF where using the names of the athletes I gathered from my initial collection I had to gather
information on the athletes individual heights as well as there personal best times, for some athletes
not as well established such as Timi Garstang his information was not accessible on the IAAF website
therefore I had to type his name in on google search engine which directed me to his national website
as opposed to the IAAF website. After I collected the athletes heights and weights I then used Microsoft
excel where I put the athletes heights in no specific order in one cell column and in the other cell
column I put the athletes personal best times. After completing the athletes heights and personal bests
I then selected all of the data and put the data in a scatter graph.
P3: Collect and record / M2: Correctly analyse & describe techniques / D1: Correctly analyse & explain techniques
Data Collection
Use your unit 4 work to help you write your detailed method.
A useful reminder of data collection techniques is linked in section 2 on page 2 here.
I carried out desk based research as part of my data collection, the data that I collected
was secondary quantitative data from sources such as the IAAF and some athletes personal
profiles, the way in which I collected the personal bests of the athletes were to search the
athletes on sources such as the IAAF. Desk based research was the best type of data
collection method for my individual research as opposed lab based or field based test. The
benefits of choosing desk based research is that the data I needed to collect was relatively
easy to gather from the secondary sources however I did have some difficulty finding data
for some athletes personal bests. Another benefit of desk based research is that there was
no cost involved in collecting the data. One of the disadvantages of desk based research is
the quality of research, the reliability of data I gathered from secondary sources such as
Wikipedia may not be 100% accurate and up to date. Another disadvantage of desk based
research is that the data I collected was not in the specific form that I needed it in. for
example I had to collect the personal bests from the secondary sources and then put the
data into my own needs for my project. The type of data I gathered was ordinal data be
ranked and put in place depending on the values that each subject has for example I was
ranking height of my sample against personal best times.
P3: Collect and record / M2: Correctly analyse & describe techniques / D1: Correctly analyse & explain techniques
Data Analysis
Use your unit 4 work to help you write your detailed method.
A useful reminder of data collection techniques is linked in section 3 and 4 on page 2
here.
For my research I had to analyse the data that I had collected from my secondary
sources. I used Microsoft excel in order to analyse my data by creating a scatter graph
the benefits of using a scatter graph is that it can be used to create the relationship
between two variables for a set of paired data for example for my research project my
set paired of data was height and PB performance. One of the main advantages of a
scatter graph is that it demonstrates a typical relationship, which is generally not so
clear in various graphing methods normally used a bar graph would not have been
suitable as a data analysis technique for my specific work. Another technique of data
analysis was central tendency, mean mode and median the advantage of this was to
distinguish the mean height of athletes involved within my research, the ,mean
personal best times of the athletes involved within my research etc.
P3: Collect and record / M2: Correctly analyse & describe techniques / D1: Correctly analyse & explain techniques
Results
.
P3: Collect and record / M2: Correctly analyse & describe techniques / D1: Correctly analyse & explain techniques
After collection and analysis, I was able to look at my results and my data to find out the relationship between height and
personal best performance of 100m sprinters who competed in the London 2012 Olympics. When analysing my results I had
gathered from my data it has left me with no clear distinction as to whether my hypothesise is 100% true. Initially I just had
my graph that I had constructed on Microsoft excel to make conclusions on my results when looking into detail at my
scatter graph it didn’t exactly fit my hypothesis. The scatter graph had two variables height and personal best time, the
graph showed that there was not a clear distinction that taller athletes had better personal best times, the data points were
scattered in many different areas on the graph which started to suggest that there is not a definitive answer as to whether
height has a positive affect on personal best performance., I concluded that there wasn’t a strong correlation in favour of
height and personal best performance however the correlation was a weak positive correlation weak using spearman's rank
correlation coefficient the correlation rank was 0.582716. There were a few outliers within my graph and some data started
to suggest that my hypothesis was true but I soon found that there was data to suggest otherwise, for example Usain Bolt
was by far the tallest athlete and also the athlete who recorded the quickest personal best time, however 50th tallest athlete
ran the 14th quickest personal best time. Therefore my conclusion was that there was no clear answer as to whether taller
athletes would have quicker personal best times. My findings weren’t exactly what I expected to find I though prior to
carrying out the research project that I would be able to find a definitive answer.
Discussion
Here you should discuss your results.
When analysing my results I had gathered from my data it has left me with no clear distinction as
to whether my hypothesise is 100% true. Initially I just had my graph that I had constructed on
Microsoft excel to make conclusions on my results when looking into detail at my scatter graph it
didn’t exactly fit my hypothesis. The scatter graph had two variables height and personal best
time, the graph showed that there was not a clear distinction that taller athletes had better
personal best times, the data points were scattered in many different areas on the graph which
started to suggest that there is not a definitive answer as to whether height has a positive affect
on personal best performance., I concluded that there wasn’t a strong correlation in favour of
height and personal best performance however the correlation was a weak positive correlation
weak using spearman's rank correlation coefficient the correlation rank was 0.582716. There
were a few outliers within my graph and some data started to suggest that my hypothesis was
true but I soon found that there was data to suggest otherwise, for example Usain Bolt was by far
the tallest athlete and also the athlete who recorded the quickest personal best time, however 50
th tallest athlete ran the 14th quickest personal best time. Therefore my conclusion was that there
was no clear answer as to whether taller athletes would have quicker personal best times. My
findings weren’t exactly what I expected to find I though prior to carrying out the research
project that I would be able to find a definitive answer.
P2: Carry out / P4: Produce
Conclusion
. Is there a relationship between height and PB performance of 100m sprinters who competed in London 2012?
There were many trends and similarities between my sources as my 5 abstracts all involved specifically
male athletes with 7/10 of my sources were had a scope of specifically elite performers such as
weightlifting and elite 100m sprinters. A very key trend that I identified within my sources were the fact
that the studies that were carried out involved a large sample size for example Paruzel 2006 had a
sample size of 189 sprinters this is also linked to Berthelot study between anthropometric
characteristics and performance in all track and field running events where the sample size was 700
athletes. Another key trend between my sources is linked to scope and what the study’s and research
did not include females 7/10 of my sources focused on males, for example Kumagai et al studying the
relationship between muscle fascicle length and sprint running performance in 37 male 100-m sprinters
did not have a scope that took into account female sprinters this is similar to Adayemi Do (2009) who’s
study was purely focusing on elite male weightlifters. The main difference between the my sources
were the sample size of the individual research study’s for example the study carried out by Taylor
MJD(2012) involved an extremely small sample size of 3 elite sprinters as opposed to the study carried
out by Paruzel (2006) had a sample size of 188 athletes.
Do your results and discussion support your hypothesis or hypotheses? If they do why and not suggest
the reasons.
When analysing my results I had gathered from my data it has left me with no clear distinction as to
whether my hypothesise is 100% true. Initially I just had my graph that I had constructed on Microsoft
excel to make conclusions on my results when looking into detail at my scatter graph it didn’t exactly
fit my hypothesis. The scatter graph had two variables height and personal best time, the graph
showed that there was not a clear distinction that taller athletes had better personal best times, the
data points were scattered in many different areas on the graph which started to suggest that there is
not a definitive answer as to whether height has a positive affect on personal best performance., I
concluded that there wasn’t a strong correlation in favour of height and personal best performance
however the correlation was leaning towards stronger as opposed to a weak correlation. There were a
few outliers within my graph and some data started to suggest that my hypothesis was true but I soon
found that there was data to suggest otherwise, for example Usain Bolt was by far the tallest athlete
and also the athlete who recorded the quickest personal best time, however 50 th tallest athlete ran the
14th quickest personal best time. Therefore my conclusion was that there was no clear answer as to
whether taller athletes would have quicker personal best times.
P2: Carry out / P4: Produce
Review (1/3)
How well did project conclusions meet project aims? (include evidence and
specific examples)
My project conclusions show that there was no definitive answer as to whether
there was a relationship between height and personal best performance of 100m
sprinters. I was initially expecting to find from my literature review of similar
research into this field, that I would be able to make a clear conclusion and an
well explained justified answer as to whether there was a correlation between
height and personal best performance. During my data analysis there were times
when I thought that my data would prove my hypothesis to be right but the
plotted data was scattered and it was difficult to get a definitive answer.
Research I conducted into the same field as my own research supported my initial
aims however some research contradicted other research.
P5: Describe / M3: Explain / D2: Justify
Review (2/3)
What were the strengths of the research project? (include evidence and specific
examples)
The main strength of my research project was that my research was closely linked to a topic that
is of keen interest in the world of science at the moment, due to the rise of Usain Bolt research
into the mechanics of not only Usain Bolt but other taller elite sprinters are becoming
increasingly popular I felt that this was a strength of my research as I could find other similar
sources of research to support my work in terms of methods and results. Another strength of my
research was that it was extremely valid and straight to the point I wanted to investigate the
affect of height on performance, both these variables height and personal best performance
were relatively easy to collect from secondary sources. The last strength from my research
project was that my data that I needed to gather for my research project was very easily
accessible and therefore I could collect my data and get on with my research quickly.
P5: Describe / M3: Explain / D2: Justify
Review (3/3)
What were the areas for improvement of the research project? (include evidence and
specific examples)
One main weaknesses of my research project is that I didn’t allow my self enough
time to complete tasks and some tasks were rushed or not done to the highest
standard. This meant that tasks were rushed, I did not set myself targets of when tasks
should be completed and my planning took a long time. Another weakness of my
research study was that I only looked at sprinters from the London 2012 Olympics and
not taken into account previous competitors in previous years Olympics this would
have allowed me to find similarities as well as differences and make comparisons
between these timescales. Another area for improvement for my research project was
my project planning template linked to unit 5 task 1, I received a referral on my first
submission due to the reliability and validity issues and the ethical and legal
considerations, they were in question as I initially couldn’t clearly justify how much
research would meet these issues and considerations, this meant my research was in
question.
P5: Describe / M3: Explain / D2: Justify
Future Recommendations (1/5)
If the project was to be completed again what would you change and why?
(include evidence and specific examples)
If I was to carry out this research project again I would definitely plan my project
better in terms of time, I would delegate specific times and deadlines of when
certain tasks needed to be completed for example I would say that my data
collection needed to be completed by week 1, my analysis of the data would need
to be completed by week 3 etc. this would allow me to work specifically to one
target as opposed to completing small sections on different parts of the research
project it would allow me to work systematically and deal with tasks that required
sufficient time first and then focus on the tasks that were not so time consuming
last. For example during my research project I did not focus on one specific aspect
of my research for example I didn’t focus on collecting the heights and personal
bests all in one go I was completing other work instead of focusing on my data
collection. Another change would be to take into account other Olympics in
previous years to see if trends have changed for example taller athletes over the
years have in fact had similar results to my findings.
P4: Produce / P5: Describe / M3: Explain / D2: Justify
Future Recommendations (2/5)
What would be the benefits of the proposed changes stated on the previous page? (include
evidence and specific examples)
The benefits of the proposed changes mentioned on the previous slide would be that I would
have been able to gather my findings much faster than I did, this would have allowed me to meet
deadlines and not rush work, I feel that I could have looked into the field of 100m sprinting more
however because at the start I didn’t plan my research project well enough tasks were rushed
and my data collection took a lot of time. Due to the fact that my data collection in terms of my
74 athletes and there heights and personal bests there statistics may have been wrong and
therefore unreliable. For some athletes who are not as well known there heights and personal
bests were difficult to find therefore I had to use unreliable sources such as Wikipedia. If
someone else was to carry this research further and use the exact method that I used in my
research I would advise them to plan there research thoroughly and set deadline for when tasks
in the research needed to be completed, this would allow there research to be deemed more
valid and reliable.
P4: Produce / P5: Describe / M3: Explain / D2: Justify
Future Recommendations (3/5)
State a proposal for further research (in total three proposals are needed and
this is number one of three)
I would like my research to be carried on and taken further as I feel that this field of research
would definitely benefit talent identification scouts picking up talent at a young age, I feel that my
research is very interesting and someone with a skill set and knowledge within this field would
definitely enjoy and relish the opportunity to take this research on further. However I haven’t got
the required skills and knowledge in this field, I would like this research to me taken on further to
conclude whether there is a strong correlation between height and performance of 100m
sprinters as in previous studies scientists have only touched on this fact and not come up with a
strong conclusion with strong enough evidence, I feel that this would be a good study to take
further in order to benefit scouts and coaches of 100m sprinters, I feel that for this research to be
taken further they must look at other Olympics games to identify key trends also looking at
female athletes to give a much larger sample size to investigate.
P4: Produce / P5: Describe / M3: Explain / D2: Justify
Future Recommendations (4/5)
State a proposal for further research (in total three proposals are needed and this is number two
of three)
I would like some sort of research to be done into how sprinters have evolved from previous
years of sprinting as I feel that people have touched on the fact that sprinters stature and frames
have changed but no research has been carried out. Initially when looking into the field of
sprinting many researches have only briefly touched on the adaptation of sprinters specifically
looking at the anthropometric factors that can affect an athletes performance in 100m sprinting.
It is a popular topic and has been of a keen interest to many athletes past and present as well as
researches as to whether records in the 100m are going to quicker and the factors that contribute
to personal best performance.
P4: Produce / P5: Describe / M3: Explain / D2: Justify
Future Recommendations (5/5)
State a proposal for further research (in total three proposals are needed and this is
number three of three)
The last proposal for further research would be to look at height and a variety of sports not only
sprinting this would benefit talent ID scouts in terms of selecting athletes/players at a young age
if research was carried out and a definitive answer as to whether taller athletes had a significant
advantage over smaller athletes. I would also like a longitudinal study to be carried out by
researches outlining in a graphical representation showing the proportion of the different
ethnicities and nations 100m winners over the years has come from, this would allow researches
to then draw conclusions about the genetic makeup of 100m winners also making conclusions
about the facilities/training and coaching accessible to athletes in particular countries.
P4: Produce / P5: Describe / M3: Explain / D2: Justify
Research Project Appendices
Appendix 1
Supporting material, hyperlinks, links to testing videos, photos of tests etc (each appendix needs
to be ‘citation referenced’ within your project pages 3-26). For example in brackets you should
write (see Appendix 1) where you need to evidence something.
You can add more appendices if you need to. Just ensure you update your contents pages.
http://www.iaaf.org/home
Appendix 2
Supporting material, hyperlinks, links to testing videos, photos of tests etc (each appendix needs to be ‘citation
referenced’ within your project pages 3-26). For example in brackets you should write (see Appendix 1) where
you need to evidence something.
You can add more appendices if you need to. Just ensure you update your contents pages.
http://alturl.com/mwhvd
Research Project Figures
and Tables
Figures and Tables 1
d squared= 27050
6x d squared 162300
n= 73
n squared - 1 5328
n(nsquared -1) 388944
spearman 0.582716
.00 > .19 Very Weak
.20 > .39 Weak
.40 > .59 Moderate
.60 > .79 Strong
.80 > 1.0 Very Strong
Figures and tables 2
Figures and table 3
9.5
9.7
9.9
10.1
10.3
10.5
10.7
10.9
11.1
11.3
11.5
11.7
11.9
12.1
12.3
12.5
12.7
12.9
1.5 1.55 1.6 1.65 1.7 1.75 1.8 1.85 1.9 1.95
100m PB
100m PB
Linear (100m PB)
Figures and tables 4
• Mean PB time – 10.38
• Mean height – 1.76m
• Mode PB Time – 9.91
• Mode Height 1.80m

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Unit 5 research structure template

  • 1. Unit 5 Research Project Worthing College Sports Science [Rob Fogerty ] 2015
  • 2. Investigate the relationship between height and PB performance of 100m sprinters who competed in London 2012? P2: Carry out / P4: Produce
  • 3. Abstract Write your own abstract for your research project here. Use the experience from the literacy review task as the basis for writing your own abstract. This should be the last part of the write-up that you complete. The aim of the study was to investigate the relationship between height and PB performance of 100m sprinters who competed in London 2012? A sample of 73 elite male sprinters who competed in London 2012 were all analysed in terms of there heights and there personal best times the study compared to set variables height and personal best performance. The data was collected by using the IAAF and London 2012 website as well as other secondary sources for those athletes who’s data was difficult to collect. Using the data that had been collected , the elite sprinters heights and personal bests were all entered into Microsoft excel and the data was then used to produce a scatter graph to see if a correlation existed, initially results from the scatter graph started to indicate that taller athletes in fact had better personal bests but the data was not significant, further investigation Using spearman's rank correlation coefficient showed the level of correlation was 0.582716 concluding that there was no significant relationship between height and personal best performance. P2: Carry out / P4: Produce
  • 4. Contents: General In this section you need to write a page by page contents page (correctly numbered for pages 3-26) Slide 3 – Abstract Slide 4 – Slide 4general Slide 5 – appendices Slide 6- figures and tables Slide 7– acknowledgements Slide 8 – introduction Slide 9 - literature review and references Slide 10 – project hypothesis Slide 11 – method Slide 12 – data collection Slide 13 – data analysis Slide 14– results Slide 15– discussion Slide 16 conclusion Slide17– review 1/3 Slide 18– review 2/3 Slide 19 – review 3/3 Slide 20 – future recommendations 1/5 Slide 21 – future recommendation 2/5 Slide 22- future recommendation 3/5 Slide 23- future recommendation 4/5 Slide 24- future recommendation 5/5 Slide 25-research project appendices Slide 26- Appendix 1 P2: Carry out / P4: Produce
  • 5. Contents: Appendices In this section you need to write a page by page contents page (correctly numbered for pages 27-32) Page 27- Appendix 2. Page 28-Research project figures and tables. Page 29- Figures and tables 1. Page 30-Figures and tables 2. Page 31-Figures and tables 3. Page 32- Figures and tables 4. P2: Carry out / P4: Produce
  • 6. Contents: Figures and Tables P2: Carry out / P4: Produce Page 31- Figures and tables 1 screenshot of spearman correlation coefficient for my individual research as well as Spearman’s ranking scale. Page 32- Figures and table 2. screenshot of my sample size on Microsoft excel showing the sample size of my participants involved within the research. Page 33- Figures and tables 3. Screenshot of my scatter graph representing to variables within my sample size showing height in correlation to personal best time. Page 34- Figures and tables 4. screenshot showing the central tendency within my sample eg mean, median, mode.
  • 7. Acknowledgements On this page you need to thank everyone who contributed to making your project a success. Think about the subjects, classmates and others that have helped you and how they helped you. Without the secondary information I gathered from the IAAF, London 2012 Olympics website and other secondary sources I would not have been able to carry out my research project. Without the help and guidance from Andy Strickland in my research project in terms of data analysis I would not have been able to get a clear distinction between my two variables. P2: Carry out / P4: Produce
  • 8. Introduction Here you need to introduce your project. What is the aim? To investigate the relationship between height and PB performance of 100m athletes who competed in London 2012. Why did you choose the aim? I chose this aim because I have a keen interest into elite sprinting it has always fascinated me as to the mechanics of what makes an elite sprinter and whether a elite sprinter has been nurtured or nature. I also chose this aim because I felt that this field or research had a lot of potential and I could draw out many different topics with my conclusions after I had conducted my research. What was the project timescale? 2 months. P2: Carry out / P4: Produce
  • 9. Literature Review and References Add a hyperlink to your WordPress literacy review here. http://alturl.com/x4qq3 P2: Carry out / P4: Produce
  • 10. Project Hypothesis What is your project hypothesis (or hypotheses)? I expect to find that in fact that height does have an affect on PB performance in 100m athletes who competed in London 2012. I expect to find that there are many other factors that contribute to PB performance in 100m athletes who competed in London 2012. Remember your hypothesis is an educated guess about how things work and what you expect to find. Your hypothesis should be what you test in your project and is therefore a testable hypothesis. A hypothesis is often written like: "If _____[I do this] _____, then _____[this]_____ will happen." P2: Carry out / P4: Produce
  • 11. Method Use your unit 4 work to help you write your detailed method. A useful reminder of the Unit 4 content is linked on page 2 here. Your method should include detailed instructions. What you are going to do, how are you going to do it, who is going to do it and when key actions will be completed. You should add relevant diagrams for any testing you do In the research project figures and tables section. 26 At the start of my research project I initially had to identify the athletes who were involved in the London 2012 100m qualifying rounds, to do this I had to go on the London 2012 website and gather the information of the athletes name and the sample size involved. After gathering the information I then had to identify the 74 athletes individuals heights and weights, to do this I typed in on google search engine IAAF where using the names of the athletes I gathered from my initial collection I had to gather information on the athletes individual heights as well as there personal best times, for some athletes not as well established such as Timi Garstang his information was not accessible on the IAAF website therefore I had to type his name in on google search engine which directed me to his national website as opposed to the IAAF website. After I collected the athletes heights and weights I then used Microsoft excel where I put the athletes heights in no specific order in one cell column and in the other cell column I put the athletes personal best times. After completing the athletes heights and personal bests I then selected all of the data and put the data in a scatter graph. P3: Collect and record / M2: Correctly analyse & describe techniques / D1: Correctly analyse & explain techniques
  • 12. Data Collection Use your unit 4 work to help you write your detailed method. A useful reminder of data collection techniques is linked in section 2 on page 2 here. I carried out desk based research as part of my data collection, the data that I collected was secondary quantitative data from sources such as the IAAF and some athletes personal profiles, the way in which I collected the personal bests of the athletes were to search the athletes on sources such as the IAAF. Desk based research was the best type of data collection method for my individual research as opposed lab based or field based test. The benefits of choosing desk based research is that the data I needed to collect was relatively easy to gather from the secondary sources however I did have some difficulty finding data for some athletes personal bests. Another benefit of desk based research is that there was no cost involved in collecting the data. One of the disadvantages of desk based research is the quality of research, the reliability of data I gathered from secondary sources such as Wikipedia may not be 100% accurate and up to date. Another disadvantage of desk based research is that the data I collected was not in the specific form that I needed it in. for example I had to collect the personal bests from the secondary sources and then put the data into my own needs for my project. The type of data I gathered was ordinal data be ranked and put in place depending on the values that each subject has for example I was ranking height of my sample against personal best times. P3: Collect and record / M2: Correctly analyse & describe techniques / D1: Correctly analyse & explain techniques
  • 13. Data Analysis Use your unit 4 work to help you write your detailed method. A useful reminder of data collection techniques is linked in section 3 and 4 on page 2 here. For my research I had to analyse the data that I had collected from my secondary sources. I used Microsoft excel in order to analyse my data by creating a scatter graph the benefits of using a scatter graph is that it can be used to create the relationship between two variables for a set of paired data for example for my research project my set paired of data was height and PB performance. One of the main advantages of a scatter graph is that it demonstrates a typical relationship, which is generally not so clear in various graphing methods normally used a bar graph would not have been suitable as a data analysis technique for my specific work. Another technique of data analysis was central tendency, mean mode and median the advantage of this was to distinguish the mean height of athletes involved within my research, the ,mean personal best times of the athletes involved within my research etc. P3: Collect and record / M2: Correctly analyse & describe techniques / D1: Correctly analyse & explain techniques
  • 14. Results . P3: Collect and record / M2: Correctly analyse & describe techniques / D1: Correctly analyse & explain techniques After collection and analysis, I was able to look at my results and my data to find out the relationship between height and personal best performance of 100m sprinters who competed in the London 2012 Olympics. When analysing my results I had gathered from my data it has left me with no clear distinction as to whether my hypothesise is 100% true. Initially I just had my graph that I had constructed on Microsoft excel to make conclusions on my results when looking into detail at my scatter graph it didn’t exactly fit my hypothesis. The scatter graph had two variables height and personal best time, the graph showed that there was not a clear distinction that taller athletes had better personal best times, the data points were scattered in many different areas on the graph which started to suggest that there is not a definitive answer as to whether height has a positive affect on personal best performance., I concluded that there wasn’t a strong correlation in favour of height and personal best performance however the correlation was a weak positive correlation weak using spearman's rank correlation coefficient the correlation rank was 0.582716. There were a few outliers within my graph and some data started to suggest that my hypothesis was true but I soon found that there was data to suggest otherwise, for example Usain Bolt was by far the tallest athlete and also the athlete who recorded the quickest personal best time, however 50th tallest athlete ran the 14th quickest personal best time. Therefore my conclusion was that there was no clear answer as to whether taller athletes would have quicker personal best times. My findings weren’t exactly what I expected to find I though prior to carrying out the research project that I would be able to find a definitive answer.
  • 15. Discussion Here you should discuss your results. When analysing my results I had gathered from my data it has left me with no clear distinction as to whether my hypothesise is 100% true. Initially I just had my graph that I had constructed on Microsoft excel to make conclusions on my results when looking into detail at my scatter graph it didn’t exactly fit my hypothesis. The scatter graph had two variables height and personal best time, the graph showed that there was not a clear distinction that taller athletes had better personal best times, the data points were scattered in many different areas on the graph which started to suggest that there is not a definitive answer as to whether height has a positive affect on personal best performance., I concluded that there wasn’t a strong correlation in favour of height and personal best performance however the correlation was a weak positive correlation weak using spearman's rank correlation coefficient the correlation rank was 0.582716. There were a few outliers within my graph and some data started to suggest that my hypothesis was true but I soon found that there was data to suggest otherwise, for example Usain Bolt was by far the tallest athlete and also the athlete who recorded the quickest personal best time, however 50 th tallest athlete ran the 14th quickest personal best time. Therefore my conclusion was that there was no clear answer as to whether taller athletes would have quicker personal best times. My findings weren’t exactly what I expected to find I though prior to carrying out the research project that I would be able to find a definitive answer. P2: Carry out / P4: Produce
  • 16. Conclusion . Is there a relationship between height and PB performance of 100m sprinters who competed in London 2012? There were many trends and similarities between my sources as my 5 abstracts all involved specifically male athletes with 7/10 of my sources were had a scope of specifically elite performers such as weightlifting and elite 100m sprinters. A very key trend that I identified within my sources were the fact that the studies that were carried out involved a large sample size for example Paruzel 2006 had a sample size of 189 sprinters this is also linked to Berthelot study between anthropometric characteristics and performance in all track and field running events where the sample size was 700 athletes. Another key trend between my sources is linked to scope and what the study’s and research did not include females 7/10 of my sources focused on males, for example Kumagai et al studying the relationship between muscle fascicle length and sprint running performance in 37 male 100-m sprinters did not have a scope that took into account female sprinters this is similar to Adayemi Do (2009) who’s study was purely focusing on elite male weightlifters. The main difference between the my sources were the sample size of the individual research study’s for example the study carried out by Taylor MJD(2012) involved an extremely small sample size of 3 elite sprinters as opposed to the study carried out by Paruzel (2006) had a sample size of 188 athletes. Do your results and discussion support your hypothesis or hypotheses? If they do why and not suggest the reasons. When analysing my results I had gathered from my data it has left me with no clear distinction as to whether my hypothesise is 100% true. Initially I just had my graph that I had constructed on Microsoft excel to make conclusions on my results when looking into detail at my scatter graph it didn’t exactly fit my hypothesis. The scatter graph had two variables height and personal best time, the graph showed that there was not a clear distinction that taller athletes had better personal best times, the data points were scattered in many different areas on the graph which started to suggest that there is not a definitive answer as to whether height has a positive affect on personal best performance., I concluded that there wasn’t a strong correlation in favour of height and personal best performance however the correlation was leaning towards stronger as opposed to a weak correlation. There were a few outliers within my graph and some data started to suggest that my hypothesis was true but I soon found that there was data to suggest otherwise, for example Usain Bolt was by far the tallest athlete and also the athlete who recorded the quickest personal best time, however 50 th tallest athlete ran the 14th quickest personal best time. Therefore my conclusion was that there was no clear answer as to whether taller athletes would have quicker personal best times. P2: Carry out / P4: Produce
  • 17. Review (1/3) How well did project conclusions meet project aims? (include evidence and specific examples) My project conclusions show that there was no definitive answer as to whether there was a relationship between height and personal best performance of 100m sprinters. I was initially expecting to find from my literature review of similar research into this field, that I would be able to make a clear conclusion and an well explained justified answer as to whether there was a correlation between height and personal best performance. During my data analysis there were times when I thought that my data would prove my hypothesis to be right but the plotted data was scattered and it was difficult to get a definitive answer. Research I conducted into the same field as my own research supported my initial aims however some research contradicted other research. P5: Describe / M3: Explain / D2: Justify
  • 18. Review (2/3) What were the strengths of the research project? (include evidence and specific examples) The main strength of my research project was that my research was closely linked to a topic that is of keen interest in the world of science at the moment, due to the rise of Usain Bolt research into the mechanics of not only Usain Bolt but other taller elite sprinters are becoming increasingly popular I felt that this was a strength of my research as I could find other similar sources of research to support my work in terms of methods and results. Another strength of my research was that it was extremely valid and straight to the point I wanted to investigate the affect of height on performance, both these variables height and personal best performance were relatively easy to collect from secondary sources. The last strength from my research project was that my data that I needed to gather for my research project was very easily accessible and therefore I could collect my data and get on with my research quickly. P5: Describe / M3: Explain / D2: Justify
  • 19. Review (3/3) What were the areas for improvement of the research project? (include evidence and specific examples) One main weaknesses of my research project is that I didn’t allow my self enough time to complete tasks and some tasks were rushed or not done to the highest standard. This meant that tasks were rushed, I did not set myself targets of when tasks should be completed and my planning took a long time. Another weakness of my research study was that I only looked at sprinters from the London 2012 Olympics and not taken into account previous competitors in previous years Olympics this would have allowed me to find similarities as well as differences and make comparisons between these timescales. Another area for improvement for my research project was my project planning template linked to unit 5 task 1, I received a referral on my first submission due to the reliability and validity issues and the ethical and legal considerations, they were in question as I initially couldn’t clearly justify how much research would meet these issues and considerations, this meant my research was in question. P5: Describe / M3: Explain / D2: Justify
  • 20. Future Recommendations (1/5) If the project was to be completed again what would you change and why? (include evidence and specific examples) If I was to carry out this research project again I would definitely plan my project better in terms of time, I would delegate specific times and deadlines of when certain tasks needed to be completed for example I would say that my data collection needed to be completed by week 1, my analysis of the data would need to be completed by week 3 etc. this would allow me to work specifically to one target as opposed to completing small sections on different parts of the research project it would allow me to work systematically and deal with tasks that required sufficient time first and then focus on the tasks that were not so time consuming last. For example during my research project I did not focus on one specific aspect of my research for example I didn’t focus on collecting the heights and personal bests all in one go I was completing other work instead of focusing on my data collection. Another change would be to take into account other Olympics in previous years to see if trends have changed for example taller athletes over the years have in fact had similar results to my findings. P4: Produce / P5: Describe / M3: Explain / D2: Justify
  • 21. Future Recommendations (2/5) What would be the benefits of the proposed changes stated on the previous page? (include evidence and specific examples) The benefits of the proposed changes mentioned on the previous slide would be that I would have been able to gather my findings much faster than I did, this would have allowed me to meet deadlines and not rush work, I feel that I could have looked into the field of 100m sprinting more however because at the start I didn’t plan my research project well enough tasks were rushed and my data collection took a lot of time. Due to the fact that my data collection in terms of my 74 athletes and there heights and personal bests there statistics may have been wrong and therefore unreliable. For some athletes who are not as well known there heights and personal bests were difficult to find therefore I had to use unreliable sources such as Wikipedia. If someone else was to carry this research further and use the exact method that I used in my research I would advise them to plan there research thoroughly and set deadline for when tasks in the research needed to be completed, this would allow there research to be deemed more valid and reliable. P4: Produce / P5: Describe / M3: Explain / D2: Justify
  • 22. Future Recommendations (3/5) State a proposal for further research (in total three proposals are needed and this is number one of three) I would like my research to be carried on and taken further as I feel that this field of research would definitely benefit talent identification scouts picking up talent at a young age, I feel that my research is very interesting and someone with a skill set and knowledge within this field would definitely enjoy and relish the opportunity to take this research on further. However I haven’t got the required skills and knowledge in this field, I would like this research to me taken on further to conclude whether there is a strong correlation between height and performance of 100m sprinters as in previous studies scientists have only touched on this fact and not come up with a strong conclusion with strong enough evidence, I feel that this would be a good study to take further in order to benefit scouts and coaches of 100m sprinters, I feel that for this research to be taken further they must look at other Olympics games to identify key trends also looking at female athletes to give a much larger sample size to investigate. P4: Produce / P5: Describe / M3: Explain / D2: Justify
  • 23. Future Recommendations (4/5) State a proposal for further research (in total three proposals are needed and this is number two of three) I would like some sort of research to be done into how sprinters have evolved from previous years of sprinting as I feel that people have touched on the fact that sprinters stature and frames have changed but no research has been carried out. Initially when looking into the field of sprinting many researches have only briefly touched on the adaptation of sprinters specifically looking at the anthropometric factors that can affect an athletes performance in 100m sprinting. It is a popular topic and has been of a keen interest to many athletes past and present as well as researches as to whether records in the 100m are going to quicker and the factors that contribute to personal best performance. P4: Produce / P5: Describe / M3: Explain / D2: Justify
  • 24. Future Recommendations (5/5) State a proposal for further research (in total three proposals are needed and this is number three of three) The last proposal for further research would be to look at height and a variety of sports not only sprinting this would benefit talent ID scouts in terms of selecting athletes/players at a young age if research was carried out and a definitive answer as to whether taller athletes had a significant advantage over smaller athletes. I would also like a longitudinal study to be carried out by researches outlining in a graphical representation showing the proportion of the different ethnicities and nations 100m winners over the years has come from, this would allow researches to then draw conclusions about the genetic makeup of 100m winners also making conclusions about the facilities/training and coaching accessible to athletes in particular countries. P4: Produce / P5: Describe / M3: Explain / D2: Justify
  • 26. Appendix 1 Supporting material, hyperlinks, links to testing videos, photos of tests etc (each appendix needs to be ‘citation referenced’ within your project pages 3-26). For example in brackets you should write (see Appendix 1) where you need to evidence something. You can add more appendices if you need to. Just ensure you update your contents pages. http://www.iaaf.org/home
  • 27. Appendix 2 Supporting material, hyperlinks, links to testing videos, photos of tests etc (each appendix needs to be ‘citation referenced’ within your project pages 3-26). For example in brackets you should write (see Appendix 1) where you need to evidence something. You can add more appendices if you need to. Just ensure you update your contents pages. http://alturl.com/mwhvd
  • 29. Figures and Tables 1 d squared= 27050 6x d squared 162300 n= 73 n squared - 1 5328 n(nsquared -1) 388944 spearman 0.582716 .00 > .19 Very Weak .20 > .39 Weak .40 > .59 Moderate .60 > .79 Strong .80 > 1.0 Very Strong
  • 31. Figures and table 3 9.5 9.7 9.9 10.1 10.3 10.5 10.7 10.9 11.1 11.3 11.5 11.7 11.9 12.1 12.3 12.5 12.7 12.9 1.5 1.55 1.6 1.65 1.7 1.75 1.8 1.85 1.9 1.95 100m PB 100m PB Linear (100m PB)
  • 32. Figures and tables 4 • Mean PB time – 10.38 • Mean height – 1.76m • Mode PB Time – 9.91 • Mode Height 1.80m