Investigating the Realtionship Between People's I.Q.s and the Amount of Television They Watch

	 Investigating the Realtionship Between People's I.Q.s and the Amount of Television They Watch
I am going to investigate into factors about people?s lives affecting and linking to I.Q. My hypothesis is that people with a higher I.Q watch less hours of television a week, have less siblings and received good Key Stage 2 results. I am investigating this line of enquiry because I am interested to see the correlation, if any, between I.Q, the amount of television watched and the number of brothers and sisters people have. Also I believe people with a higher I.Q would be more intelligent, therefore receiving higher Key Stage 2 results, and would like to see whether I am right or wrong to believe this. I assume they would watch less hours of T.V a week if they have a higher I.Q, as I believe they would be spending more time doing homework and revision. Also I think the higher the I.Q the less siblings they will have because I think they would receive more encouragement from their parents. I aim to avoid bias in my investigation by following certain sampling methods. However there are some factors that could still cause bias that I cannot change/prevent for example if there are errors in the population or dishonest answers as the data I am using is a census questionnaire. Also some key stage 2 results have been left blank, therefore I am going to assume that all blank fields equal nothing which could be caused by them not taking the exam, so this may effect my results and graphs. Another thing I assume for my hypothesis is that people?s families are all living together including all siblings.This could cause an effect on things such as amount of TV watched if they do/do not all live together but this is a factor I cannot tell from the census. To determine a population for my course-work I shall be using secondary data, a questionnaire filled in by pupils at Mayfield High School, which contains a lot of information about different aspects of their life, for example how many siblings they have, hair colour, eye colour, Key Stage 2 results and so on. The specific fields I require to investigate my hypothesis are: ? I.Q ? Average number of hours of T.V watched per week ? Number of siblings ? Key Stage 2 results in English, Maths and Science As there are 1183 pupils who filled in this questionnaire I shall use other fields, to help sort my data into smaller, more manageable samples as 1183 is far too larger number to work with. The other fields I will use are year group and gender as I intend to split all the pupils into their 5 different year groups (7, 8, 9, 10 and 11) and then into boys and girls within the year groups. This will give me 10 groups. I shall then take a systematic sample from each of the 10 groups. To determine my nth term, used in my systematic sampling I shall roll a dice and use this number for my selections, for example if I rolled a 4 I would take every 4th pupil?s data until I reach the total amount of data required from each group. I have decided to take a total of 15 pieces of data from each group, leaving me with a total of 150 samples, which is just over 10% of the total number of pupils at the school. This way I shall get an equal spread of boys and girls from each year group. If I were to take a percentage from each year group, or even from each of my 10 groups, I would end up with more pupils from larger groups, leading my results to be bias towards a certain year group or gender, as each year group is a different size with unequal amounts of each gender. Once I have followed my sampling methods, cut my results down to my final 150 and remove unneeded fields, which I will display on a separate spreadsheet, I shall then represent and compare my data in different graphs to make it simpler to interpret its relation to my hypothesis. The first thing I am going to do is copy my data into MS Access so that it is easier to sort, making it easier to create my graphs. The first graph I am going to create is a cumulative frequency curve, showing I.Q. This will enable me to calculate the average I.Q. To create this graph I will create a table in Microsoft Excel by splitting I.Q into the following 7 groups: 0

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