I have an assignment for school in which we have to do graphs, analysis correlations etc. on 2 topics with a correlation. (ie. smoking and lung cancer) or (education and income)or (pollution and public transportation) I am looking to do a topic running related but one that i can find good info for, i was thinking like bmi and 5km time or bmi and marathon time, anyone have any ideas?
Number of miles run/week vs. number of hours/week spent calling U.S. runners "pussies". Hint: it's a negative correlation.
Not running related but:
Ice cream consumption vs. number of drownings
5k times are easy to find on the web but good luck getting the bmi stats for the people who ran those times.
5km time and VO2max
1. amount of distance run and success in attracting a member of the opposite sex (or same sex, if that's how you roll)
2. 5k time and amount of soda you drink
3. amount of sleep and running success
4. length of events you run vs. bmi
5. amount of time spent on letsrun and success in school
How about the correlation between runners who grew up in a divorced/dysfunctional/addictive household, vs. those who did not...
I've learned a lot about this topic and it's really interesting.
You have to be able to collect the data to do the project, so I'd chose data that is available in the race results. Maybe age and time or something like that.
if you are going to do a running one you need one that you can find all the data easily. bmi and 5k time might be interesting, you could limit your study to a specific 5k. since results are all over the net you can get that info easy, but getting bmi data will be tough.
i would suggest something like age and marathon times or something similar.
marathonguide.com has done the work for you.
http://www.marathonguide.com/features/Articles/2006RecapOverview.cfm
take a look at the article and the data they collected. tie age to something. for example, the average person runs his best marathon when between 40-44 as that is the fastest male age group. you could do the same analysis for females-age and marathon times.
you might want to compare the results you come up with as against how it was in 2002 (the oldest yearly report mg has).
http://www.marathonguide.com/features/Articles/2002RecapOverview.cfm
http://www.marathonguide.com/features/Articles/2003RecapOverview.cfm
http://www.marathonguide.com/features/Articles/2004RecapOverview.cfm
http://www.marathonguide.com/features/Articles/2005RecapOverview.cfm
if you look at each report you can find a few trends - slowing average times, more women, more marathons, older age groups running the fastest times...
Average running time of the top 100 (or 25 or 50)runners in the New York Marathon (and/or Boston/London etc) since they started, correlated to the numbers of runners in the field.
Are the times getting faster or slower?
thanks, ya i want something were i can get alot of facts and numbers.
OK, well let's focus on things you could easily get data for, at a number of different levels.
At a race level, you easily can get age, sex and time by runner. You could do some interesting analysis on how winning times change with age, how average times change with age, or even how the variance or % difference in time between the winning and average times changes with age. You could also examine how the differences in times across the sexes change with age. Bear in mind that some of those relationships won't necessarily be linear, and others will show no relationship (which will be interesting in itself).
With a bit more work you could do some comparisons across races, to investigate things like how does the number of runners in a race impact winning time and average times, and what impact does climb, temperature, altitude or other environmental factors have on the winning time?
You could also get some datasets of elite runners, which would give you PBs, race history, year bests, weight and height. So you could analyse things like the impact of BMI on PB, the optimum age for a marathoner, the optimum number of marathons to run per year.
Finally, you could look at data across countries, and look at influences on national records at a given distance, such as population, GDP per head, average BMI, even temperature. This would be a good dataset to do multivariate analysis on if you're at that level.
Hope this helps.
You could go to a track meet and count strides per minute for different events.
Tim_sleepless wrote:
OK, well let's focus on things you could easily get data for, at a number of different levels.
At a race level, you easily can get age, sex and time by runner.
that is key. you need something that you can get the data easily. think about what data is easily available and then what you can compare/contrast with that data.
you can get age, sex, time for a given race, you might be able to get results from 10 years ago for the same race and do some comparisons across time that way as well.
the paper/project would be better if you did a basic analysis over one race, then did the same analysis in the same race from 10 years prior and discuss how/why things changed.
find a local race if you can.
How about running and grades? Seems like there has been some studies in this so maybe data is available. Number of miles vs GPA or local, state, national ranking vs. GPA.
wow thanks for all your suggestions
running and death
you will find the correlation to be 100%
The amount of prize money at a race and the number of Kenyans who show up.
Porky Pigging wrote:
5k times are easy to find on the web but good luck getting the bmi stats for the people who ran those times.
Height and weight measurements are on T&F News' website...you could do a correlation between BMI and any sort of time, race distance, etc.