1183 (Total students at ‘Mayfield High School’)
This all equals 15.3 which is not a whole number. So I have rounded it down, as I have done for all my data that is not a whole number. This gave me the answer of 15. Through this I know that I will take a sample of 15 student’s heights and weights from the boys in year 7. To find out the sampling sizes for the girls and for other year groups I will then use the same method and round the number I get down. The numbers I got were as follows:
After Finding out how many I would be sampling from each year and gender I went and found out the random students from each year and gender. Bearing in mind the more students that I will sample the more reliable my data will be in proving my hypothesis, I learned of certain methods I could use to get the randomly chosen children that I would be basing my hypothesis on. The idea I used to find these numbers was (Ran# x Group Size) + number in previous group. For year 7 boys there was no previous year so I added 0, this is what the equation looked like (Ran# x 151) + 0. For my second group (Year 7 girls) I had a previous group to add onto it so the equation looked like this (Ran# x 131) + 151. I maintained this same formula throughout my year groups. I received random numbers with decimal points on them so I rounded down, which is the method that I will consistently do throughout my Data Handling Coursework.
After doing this the 15 numbers I received from year 7 boys were student number (in order of how I received them): 1, 36, 93, 39, 10, 85, 44, 121, 80, 43, 107, 47, 43, 93, and 34.
I then went on to year 7 girls the 13 numbers I received were student number (in order of how I received them): 193, 202, 156, 281, 267, 208, 167, 279, 233, 210, 219, 163 and 172.
I then changed year groups to year 8 and received 14 numbers for the boys in that year group were student number (in order of how I received them): 393, 376, 421, 293,409, 325, 417, 364, 288, 424, 375, 414, 425 and 392.
The 12 numbers I received from the girls in year 8 were student number (in order of how I received them): 487, 441, 499, 478, 485, 518, 534, 518, 537,460, 441 and 519.
I then changed year groups for the second time and received 11 numbers for the boys in year 9 which were student number (in order of how I received them): 557, 570, 632, 622, 632, 638, 649, 558, 573, 570 and 630.
The girls in year 9 gave me 14 numbers that looked like student number (in order of how I received them): 702, 711, 777, 716, 741, 748, 771, 715, 712, 791, 747, 729, 760 and 753.
The year 10 boys gave me 10 numbers that looked like student number (in order of how I received them): 853, 905, 830, 893, 856, 870, 861, 862 and 886.
The year 10 girls gave me 9 numbers that consisted of student number (in order of how I received them): 1,005, 924, 942, 993, 950, 976, 932, 955 and 999.
The last change of year groups saw me with year 11 boys the 8 numbers that they gave me were student number ( in order of how I received them): 1,082, 1,089, 1,017, 1,034, 1,087, 1,055, 1,060 and 1,089.
The last numbers I received were from the girls in year 11 and they were student number (in order of how I received them): 1,168, 1,106, 1,137, 1,177, 1,137, 1,160, 1,172 and 1,114.
In some circumstances there were replicates which I had to delete. This left the number of students from each year down to: Year 7 Boys-13
Year 7 Girls-Remained 13
Year 8 Boys-Remained 14
Year 8 Girls-10
Year 9 Boys-9
Year 9 Girls-14
Year 10 Boys-9
Year 10 Girls-Remained 9
Year 11 Boys-7
Year 11 Girls-7
Total-104
After finding all my numbers I started to decide on the different hypothesis I could use and how I could test them. Once deciding the best one which would give me the best and most data and how I would test it, I started to think about the graphs I should use to prove my data. I decided to use the different types of graphs that would make it easiest for other people to understand and graphs where I could express my data handling skills in the best and most accurate way. My chosen types of graphs were Line Graphs as these are easy to read from and show different types of data handling skills such as finding the mean, mode, medium, range, upper quartile, lower quartile, inter quartile range and line of best fit. I will use this graph as I think it will be one of the prosier in either proving or disproving my hypothesis.
My second chosen graph that I will use to evaluate whether my hypothesis is true or not is a scatter graph. I decided to use a scatter graph as I think that it would be a useful tool for comparison between two different kinds of data. As this is a good tool for comparison I thought that this would be another good way to show my data handling skills and try and prove my hypothesis.
My third graph chosen to try and prove my hypothesis is a Histogram. I chose to use this type of graph because it will be able to show people the more reliable data out of the data present for genders and year groups. This will also allow me to show added skill in data handling such as mean dispersion and vertical dispersion. The graph is also easily converted into a frequency polygon which will give added information.
The next graph chosen to try and prove my hypothesis and show my data handling skills was a cumulative frequency. I decided to use this graph as it’s the best way in presenting the lower quartile, the upper quartile and the inter quartile range. It also a way I can use another graph I wanted to use which is a boxplot. The reason I chose as my fifth graph to be a boxplot is because it represents a visible view of my data shown in the cumulative frequency graph. I will use it next to my cumulative frequency in order to show this.
The last graph I will use is a stem and leaf graph as this is a good way to show the comparison between data aswell and is again very easy to show some of my data handling skills. This is also a better graph to comment on because it is easy to write about as it is neat and easy to see all data how you want to see it and show off some of the techniques I have learnt about this graph.
After I have designed these graphs commented on all them and shown my data handling skills I will have to write up my conclusion. This will consist of what I have found out about my hypothesis and the new skills I have learnt through this coursework project. At the end of my coursework I will have an introduction, my results about my hypothesis and finally conclusion.