Since I want to obtain a larger amount of results for this main investigation, I will be using the results of all of the six weeks. However, I will have to vary the amount of results taken each week according to the number of the Premiership results that will be taken. I will be taking results from the Premiership, Division One, Division Two, Division Three, and the Nationwide Conference. The results will hopefully show me a trend which I will be able to point out in my conclusion for this investigation. I have already stated my prediction previously and I will now see if they are true or not.
The first week, DECEMBER 2nd 2002, shows that there were nine fixtures in the Premiership. Due to there being nine premiership fixtures that week, I will have to take nine from each other league to analyse and put down into my table of results. The second week, DECEMBER 16th 2002, shows that there were also nine fixtures; this means that I will take nine from the other leagues as well to analyse.Week 3, DECEMBER 21/22 2002, is the only exception, this week has got the least amount of fixtures in the Conference league, this means that the same amount of the Conference league fixtures have to be taken from the other leagues as well. Therefore, since the Conference ha a total of eight fixtures that week, I will take eight results from the other leagues as well.
Week 4, DECEMBER 26th 2002, has ten results meaning ten will also be taken from the other leagues each. Week 5, DECEMBER 28/29 2002, also has ten results which means that ten results will have to be taken from each league. The sixth and final week, JANUARY 18/19 2003, has ten results in all and so ten results from each league will also be taken for analysis.Each league will have a totally random starting point, which I will chose, and from there, the relevant number of results will be taken down for analysis. I will list the weeks in order and the leagues in order, then I will show the random starting point and from where to where the results were taken. For example, in the Nationwide Division One, I would pick a random starting point, e.g.
the starting point is Brighton vs. Burnley, and then the end point would be Wolves vs. Bradford. The results will be taken consecutively after the start point in a cluster.
I will be going down the resource book; this will mean that the results will be taken in order for consecutive results.I will take the results and then use the times that are given of the goals scored and then add them to my table of results. The table of results will be the same as they were when I had carried out my pilot study. From this I mean that the table used in my pilot study will be the same as the one that I am going to use for the main investigation. The only difference will be that I will add more rows for the addition of the new leagues that will be added into this part of the investigation. I will also make one slight adjustment, although I will keep the 41-50 minute period of time, I will make two extra columns which ultimately split that ten minute period into two five minute periods of the 41-45 minutes of the game and the 46-50 minutes of the game. This is so that I can see clearly overall in what half most of the goals on average are scored within.
NB: POSTONED MATCHES WILL NOT BE ACCOUNTED FOR DATA PRESENTATIONI have carefully checked my results and have now presented them in different ways. I have used pie charts drawn by hand and made on the computer, and I have used bar charts, line graphs and tables to present my data, these have been done by using the computer. I have used different methods to show the same data because I want to get different views of my data so that I can see every aspect of the data and not miss out any points in the data.The pie charts were used to show a clear difference in the data, however, the only disadvantage would be close data.
If two or more sets of data are closely matched, then it is hard to tell which is greater. However, the pie charts do clearly show the data and show clear differences when there is a supposed to be clear differences in the data. A disadvantage that comes when hand drawing the pie charts would be the amount of time that has to be taken to calculate the angles of each data and then drawing and colouring in the charts. Otherwise, pie charts are good for presenting data. One last advantage for the pie chart is that if there is only two sets of data, then a clear difference can be seen much more easily between the two values, whereas with more sets, it becomes harder to see which set of data is the greatest and so forth.Bar charts and line graphs are more or less the same type of things; I prefer the line graphs over the bar charts. They both clearly show the differences in data and one can easily see what data is greater, the numbers on the axis help as well to determine the data value.
The difference is that the line graphs are make it easier to determine the greatness of each set of data. For example, on a bar chart if there are two sets of data next to each other on the chart, and if they were both more or less evenly matched, then it would be very hard to tell the difference in value between the two. The line graphs have lines to show even the slightest changes in value.This means that the problem is eliminated, the line graphs are very good ways of presenting the data.
I have used the chosen methods to present my data solely because they are clear and easy to understand. This is why I have used the certain methods to present the data that I have. From these presentation methods, I will be able to easily analyse the results and then hopefully draw up a conclusion.DATA ANALYSISAfter looking at my different presentations of the data that I have created, I can see that there are clear answers to my investigations.
The data is shown in very clear ways, I can easily interpret what each graph, chart or table shows me and this is what is going to help me to draw up a conclusion. The sub investigations were to find out in which half the most amount of goals were scored, whether they were scored mostly in the first half or mostly in the second half.The second sub investigation was to find out which league brings the most goals.
By this I mean, I want to find out the league in which the most goals are scored, this will be seen through the presented data in all its forms. Hopefully by analysing the data correctly I will be able to figure out the answers to my investigations, including of course, my main investigation which is of course to find out in which ten minute period in all games, the most number of goals are scored (in a football match based on the data).After looking at my data and carefully analysing it, I can see the answers to my investigations. For my sub investigation which asks to find out which half the most amount of goals were scored in, I can clearly see that there is a trend which shows in each league, as well as overall, that the most amount of goals are scored in the second half rather than the first.
This is easily seen through the pie charts that have been made on computer.The second sub investigation asks what league brings the most goals. By looking at the graphs, I can see that the league that brings the most amount of goals was the Conference League. This can be seen very clearly from my line graphs and so the sub investigation has an answer to it. The main investigation also gets its answer from the charts that I have made. The investigation asked in which ten minute period the most number of goals were scored in. I have found due to my graphs that the most number of goals are scored within the last ten minutes of the game. This is shown, like I have already stated, in my charts that I have created for the data and it is clearly shown within them.
CONCLUSIONAfter analysing my data, I have finally come to the conclusions to my investigations. For the first sub investigation, which was to find out in which half of the game the most goals were scored, my analysis shows that the most number of goals are scored in the second half of the game. This follows my prediction, thanks to my pilot study; I had made the correct prediction for the investigation. The prediction was correct and this is shows from the conclusion which shows that the majority of goals were scored in the second half rather than the first half. Fortunately, all of the leagues show that most of their goals were scored in the second half, this means that there are no anomalies and all the leagues follow the same rule.
The second sub investigation was to find out which league brought the most goals overall. I had predicted that the further down in footballing standards one went, the more goals there were likely to be. Once again, this prediction had come from the pilot studies that I had carried out and once again the prediction was correct.
From analysing my presented data, I can see that the most amounts of goals that were scored came from the Conference League, which is the lowest in football standards out of the leagues chosen. This goes to show that my prediction was correct. From the graphs and the table, we can see that the number of goals increase as the standards drop, however, at Division Three, there is a slight anomaly.The number of goals that were scored in Division Three, were fewer than Division Two, this means that the rule of more goals being scored as standards dropped, was not being followed by this league. Fortunately, this was just a lone anomalous point, and because all of the other leagues followed the rule, it showed that the rule was in place and that the conclusion had been found.
Therefore, after analysing the anomaly to find that there was no problem to the rest of the data, I can say that my prediction was correct that the greatest number of goals would be scored in the Conference League due to the rule.The main investigation was to find out which ten minute period of a football match the most number of goals were to be scored. After setting my prediction solely on the outcome of my pilot studies, I had said that the most number of goals would come in the last ten minutes of the game.
From looking at the table and the graphs and charts, I can immediately see that the most number of goals came in the last ten minutes of the game. This is supported very well because each league follows this rule, so there are no anomalous points and the conclusion is easily discovered. These are my conclusions to my investigations.EVALUATIONMy investigation was very successful and I have taken the right approach towards it, the statistical approach. I have seen my faults in certain areas and then I went on to correct them for the main investigation, these mistakes can be seen in my appendix. My draft investigation was based on the same questions; however, I had planned to carry it out in a different manner.
The investigation itself was a good one. It really did test my statistical knowledge and made me use that knowledge to get answers for the investigations. I had to use tables and then draw up graphs and charts from the data that was within them. I also had to use a no biased way to gather my data (data sampling). I had to think what type of graphs and charts were going to be used in accordance to the data at hand, and I think that overall I have used my statistical knowledge well to plan the investigation and carry it out in the right manner.
I do think that a few extra graphs and charts could be added for each set of data; however, I have only done this for the main investigation not the sub investigations. The reason for this is simple; I want to spend more time on the main investigation than I do on the others. Sometimes, adding too much to the sub investigations makes it harder to analyse the data and it is a very long process to create and analyse them.I have used the certain graphs and charts that I have due to their relevance with the data. I thought that the graphs and charts would show the relevant data clearly and in the most efficient way, I had many other types of presentation methods which I could use, however I only used the ones that I had because they are more efficient in data presentation. I have hand drawn a set of pie charts so that I can test my own understanding of how to draw up charts with set data, this has proved successful as I see that I have managed to produce sufficient pie charts to go with the data.I have come to my conclusions for each of the investigations due to careful planning of my pilot studies and then careful analysis of them.
I have taken relevant predictions from the results of the pilot studies and I have also taken the same layout of the pilot studies for my main investigation. These have worked well to show me to my conclusions. Due to my pilot studies and planning I have seen that the whole investigation became very easy. This is how I came to my conclusions so easily.