As the task above states, I will be looking at how certain populations perceive time, in this case 30 seconds. For this project I will be looking at data from the age range 15-18. It would be appropriate for this mathematical project to get data from every person in every age range in the entire would but this is almost physically impossible and is certainly impractical for this project. Due to language barriers, the amount of time and money it would consume and also that some age ranges such as under the age of 7 would find it difficult.The reason I have chosen the age range 15-18 is mainly due to practical purposes, the data is easily obtainable due to the fact that I am studying at a college with hundreds of people in that age range.

Although it would have been possible to include data from younger students at college, I decided to use age 15 as my lowest parameter since a certain degree of maturity was required in order to collect the data in a reliable way.I chose to study 18 year olds because will have had an extra 3 years of education and experience which should bring about a noticeable difference between the groups The children I will be studying will all have had very similar experiences with their education i. e. within maths. I have also chosen to only study boys to minimise all factors other than age.

I am also going to take some data from people over the age of 25 to see if there is a significant difference between the groups. This will be looked at to see the difference between adulthood and childhood.This data will be collected from people who work at the same place (laboratory at heartlands hospital) this will be done to minimize as many variables as possible. If I had more time I would collect data from a selection of different schools to see if education has any effect on time perception. I will collect the data by asking individuals to estimate when they think 30 seconds has passed from when I say go.

I will attempt to not let each student know what they will be doing as it will give them no time to practice and will also not announce what time as estimated in front of other students as it could give them an unfair advantage.Overall I fell this project has gone very well, the data was collected efficiently and the data processed into efficient charts, tables and graphs. The original data collected was only for two age groups ages 15 and 18, however, I felt that this did not give a very large range, even though I wanted this project to be based mainly around youngster, so I used data from people over the age of 25. This area is one of the first problems I encountered, the data set name is 25+, and I took this data from ages of 25 (my cousin) to over 70 (my Nan).If I were to do this test again, I would use a lot more age ranges and have them as close to each other, but due to time and availability I could not do this.

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The second problem I faced was the age 18+ group, as this experiment was started in year 12, many of the students of the college had not reached 18 and was there for hard to get data fro the same school, therefore out of school sources were used. If I was to do this again I was have an equal amount of data form two different schools to see if education had any effect on the estimation ability.The results I did collect however, were quite good, they were good enough to make a number of graphs including scatter graphs and cumulative frequency graphs, as well as making calculations for mean, median and mode. Looking at the graphs we can conclude that the age group 25+ had the best mean average estimation of time with less that a second away. We can also see that age 15 is the worst being at around 5 seconds off.

So we can conclude from looking at this experiment that estimation improves with age. However, as we did not look at a very old age group eg 85+, we do not to the full extent of this claim.