GCSE: IQ Correlation
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This data has been stored on a computerised data base where I can get a large quantity of data, and the data is easy to find. However, the accuracy of the data may not be known. My data will be reliable and not biased as I will use stratified sampling for each data group. I will only have some qualitive data, such as the names of pupils, however this will not effect my conclusion, whether these qualitive data are different.
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Year 10 at Stamford school and Stamford High School represent a small sample of year 10 pupils in England. Year 10 in the Stamford Endowed schools is an accurate choice as every person has have the same education and experience and the data is very easy to collect. Every person has used the same facilities, books and material and the teachers have all been taught the same. Although there maybe some problems and anomalies with this sample because someone maybe away, someone maybe blind or have eye problems and someone might be handicapped. For each question I will use a certain sample of year 10's at Stamford Endowed schools.
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94,105,100,102,102,100,103, 102, 90,107, 107, 106, 79, 99, 101, 106, 108,85,106, 100,93,107, 116, 100, 116, 112, 105, 108, 103, 90, 97, 95,102,102,100,99,102, 100, 90, 94, 103, 116, 106, 91, 91, 113, 105, 101, 107, 100, 90, 100, 103, 110, 104, 116, 113, 117, 101, 83, 106, 94, 92, 101, 112, 116, 104, 110, 117, 100, 114, 119, 112, 104, 104, 101, 108 Then, I draw a stem and leaf diagram to group the data. Stem and leaf diagram 6 7 8 9 10 11 12 9 9 3 5 7 8 0 0 0 0 0 1 1 1 2 3
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I took a sample of 50 students from Mayfield high school, 10 from year 7 to year 11. I split them into girls and boys so all together there were 25 girls and 25 boys, 5 girls and boys in each year. I used the random number generator to get all of this sample by typing in the calculator 'Shift' 'Rand#' then when you get the number you times it by how many there are in the sample. Say there are 200 then you would do 'shift' 'rand#' times 200.
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4. Hypotenuse = 4² + 6² = 52 = V52 = 7. 2111 cm Perimeter = 4+6+7.2111 = 17.2111 cm Area= 1/2 x 4 x 6 = 12 cm ² I.Q. = 4 x ? x 12 17.2111² I.Q. = 0.5090 5. H = 8² + 12² = 208 = V 208 = 14.422 cm P = 12+8+14.422 = 34.422 A = 1/2 x 8 x 12 = 48 I.Q. = 4 x ? x 48 34.422² I.Q. = 0.5090 6. H = 3² + 2² = 13 = V13 = 3.6 P = 3+2+3.6 = 8.6 A= 1/2 x 2 x 3 = 3 I.Q.
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Example females would be more precise in estimating lines and angles. For this reason, this would be a factor affecting the males on estimating lines and angles. * Job -the type of job would affect how accurate the estimate is. Example if you are doing a job where your eyes are affected i.e. I.T job, this would create problems for your eyes because they get damaged, therefore affecting your estimates. Hypothesis Hypothesis 1-People estimate the length of lines better than the size of angles Hypothesis 2-Males are better than female in estimating the angles and lines Choice of length of
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After creating a new SPELL score I shall test it to gain validation. Hypothesis My hypothesis is that most of the SPELL's point system has unfairly given letters inappropriate amounts of points. I suspect that letters such as E, T and A are going to come out very common and be awarded a low score while letters such as Z, Q and X are going to be very uncommon and result in being awarded high scores. Method To gather data I will need to use various sources form a wide range of possible sources.
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Another way that I could use to support my correlation between gym hours and weight. I would find the mean of gym hours and weight: Mean of gym hours: 10, 12, 14, 14 = 15 Mean of weight: 58, 63, 64, and 65 =62.5 Here it is also saying that in 15hrs at the gym will make you loose 62.5 pounds of weight. Medium of gym hours :( D2:17) = 2 Medium of weight: (E2:E17) = 63.5 Interquaritle range: To find the interquartile range of weight: Lower quartile range on weight: 1/4(N+1)
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Now I will see whether there is correlation between the IQ scores and the English scores. IQ English 89 3 103 4 98 3 108 5 94 3 91 4 116 5 104 4 103 5 90 4 97 2 116 5 94 4 113 4 106 5 95 4 105 4 101 4 As seen above there is correlation between the IQ scores and the English results as there is positive correlation proving that if you have a higher IQ you are more likely to achieve good results in English. My Hypothesis I will now use raw data from my school (the Swaminarayan School).
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In general, the roles in modern society suggest that men should be domineering, aggressive, better at maths and sciences, should become successful in their careers and should control and suppress their emotions and feelings. Women, on the other hand, should be submissive, nurturing, gentle, better at languages and the humanities, emotional, and desirous of nothing more than a happy family and a husband to provide for her, while she remains at home and tends the house and children. These sex-type roles are perpetuated and reinforced by the mass media and society in general in many ways.
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The 3 statements I am going to investigate are: -Does the gender of the student have an affect on their KS2 result in English?Do students who do well in Maths, also do well in Science?How does the IQ of the students affect their results?
I have chosen these sources of information because although I was given a lot of variables to choose from, I found that the amount of TV watched, the height and the weight of the students were irrelevant to my coursework. I know this data is reliable because it was retrieved from the Edexcel website. I will use a sample size of 50 students, which will be chosen at random using the random key in the calculator. By dividing the number of male students in Year 10 by the total amount of students, and then multiplying that by the sample size 50, I was able to get the number of male students I should have in my investigation.
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The Statistics are as shown below: Year Group Number of students Males Females Males %** Females %** Males needed** Females needed** 7 282 151 131 54 46 13 11 8 270 145 125 54 46 12 11 9 261 118 143 45 55 10 12 10 200 106 94 53 47 9 8 11 170 84 86 49 51 7 7 *Out of a total of 1183 students **Rounded to the nearest whole number Above is the representation of the entire year groups, to improve this investigation further, I can include a further variable of race, which would also give
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HYPOTHESIS Blonde girls are more intelligent than non blonde girls. Blonde girls that have a higher IQ watch comparatively less television. This will not be the case however for non blondes as there will be little or no correlation.
Problems could occur as different results from the different parts of the investigation could appear to contradict each other and therefore I will have to choose which one is best to follow. For example: if one should measure the spread of data in terms of the middle 50% and compare that or if one should measure the full 100% and include the outliers which could cause an inaccurate and therefore wrong conclusion. Also, different styles of graph will focus on different parts of the data and forming a general, all encompassing conclusion and thus proving/disproving my hypotheses could prove difficult.
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This experiment will show that there is a significant positive correlation between males and females who perform well academically and those who gain a high point score on a self-esteem Questionnaire
and the Coopersmith self-esteem inventory (1967/1981). The Coopersmith self-esteem inventory was developed through research to access attitude toward oneself in general, and in specific contexts: peers, parents, school and personal interests. It was originally designed for use with children, drawing on items from scales That were previously by Carl Rogers. Respondents state whether a set of 50 generally favourable or unfavourable aspects of a person are 'like me' or 'not like me'. There are two forms, a school form for ages 8-15 and an adult form for ages 16 and above.
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A typical intelligence test asks a variety of questions, many of which are of the type one learns to answer in school
The definition from Hebb is that it has two meanings, one being "an innate potential, the capacity for development, a fully innate property that amounts to the possession of a good brain & a good neural metabolism"(cited in Heim, 1970, p24) the second meaning is, the functioning of the brain which has developed with the influence of experience and maturity (cited in Heim, 1970) which is similar to Cattels (cited in Detterman, 2005 ) theory where he proposes that fluid intelligence is an innate intellectual ability and crystallised intelligence, as knowledge gained from experience (Letts, 2004).
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I will repeat this for the remaining year groups to complete my stratified sample. Once I know the amount of students from all the different year groups I will use a calculator to generate random numbers for my data. Hypothesis 1 The higher the IQ, the higher the average SATs results. There will be a stronger relationship between the girls' IQ and average SATs results than the boys'. To prove my first hypothesis I am going to plot IQ against the average SATs results on a scatter graph. I am doing this to see any correlation between the two.
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A bigger sample is required to check whether hypothesis 1 was correct. Hypothesis 2- IQ levels of pupils doesn't depend on whether they are left or right-handed. In year 7 the mean IQ is higher for the left-handed (LH) then for the right-handed (RH). In year 9 it is the other way round. In year 11 the means are about the same for both the LH and RH groups. Hence, hypothesis 2 was correct. Hypothesis 3- There will be a higher number of children with an IQ lower than the mean for their year group; in all years; however there will be some pupils with a high IQ which will increase the mean.
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to produce scaled scores. Ebrahim's Verbal scaled scores (41) gives a Verbal IQ of 89 and places him at the 23rd percentile, his score is below average as it means he scored higher than only 23 out of 100 children from the standardisation sample, in this case, his age group. Ebrahim's Performance IQ was 53 at the 0.1st percentile which is an exceptionally below average score. In result, his Full Scale IQ score was 67 at the 1st percentile; once again his Full Scale IQ score is very much below average, only scoring higher than 1% of the standardised sample.
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Firstly I will have to work out my stratified sample. I chose the sample size of 60 because I believe it will be a viable size. YEAR 7 282 x 60 = 20.8 (rounded up to the nearest whole number as 21). 813 This means that I should take 21 pupil's sets of data from year 7 for my stratified sample. YEAR 8 270 x 60 = 19.9 (rounded up to the nearest whole as 20) 813 This means that I should take 21 pupil's sets of data from year 8 for my stratified sample.
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Band A = 42 Band B = 54 Then, I need to find out exactly how many pupils from both Bands A and B that were entered into certain math tiers. They range from tier levels 3-5, 4-6 and 5-7. Maths entry levels TIERS 3-5 4-6 5-7 Band A Band B TIERS 3-5 4-6 5-7 Band A 21 8 13 Band B 21 16 17 As all the pupils are doing different tiers to one another I need to use a certain equation to find out my stratified sample size of 30 pieces of data.
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In order to do this, I will divide the population into groups which have something in common. Simple random samples will then be taken from each group. The number taken from each group must be proportional to the size of the group. This is a useful form of sampling as it is relatively simple and is often used to represent more complex populations. A disadvantage of this sort of sampling is that I may get "clumps" of data, but I will try and avoid this. Another problem I must investigate is that of age. The separation age of the school years (how to determine which year a student should be in), is September 1st.
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However, they were only able to take into consideration measurable factors, and excluded such aspects as looks and luck, which also might have an impact on the earnings of individual. Some researches have found that IQ level has little but not insignificant influence on the future income, and that individuals with higher IQ however tend to earn more (Dickens, Kane, Schultze, 1995). One's personality traits and character are said to be a one of the major determinants of who succeeds on the job and who fails (Goleman, 1998).
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The purpose of this investigation is to find if there is any correlation between two variables extracted from 5% random sampling of the Mayfield Data provided.
In this coursework, I will need to include and use the data below: * Intelligence Quotient (IQ) * KS2 results in English (level) * KS2 results in Mathematics (level) * KS3 results in Science (level) * Average number of hours of television watched per week Random Sampling Method Due to the fact that there is too many data to analyse, we were asked to take 5% of the data - a reasonable amount so that the results are meaningful and represent the whole population.
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Using the data from Mayfield High School, I am going to be investigating the relationship between IQ level and Key Stage 2 results.
x 60 9 60 This table shows me how many pupils I need from each year group. To start off with I gave each student a number from 1 - 1183, I then sorted the data into year groups and then I generated a random number between 1 -1183 using my calculator. In order to see if there is any relationship between Key Stage 2 results and IQ I am going to draw scatter diagrams. I will draw a scatter diagram for the entire school as well as one for each year group. I am doing this so that I can see if the correlation is the same across the year groups.
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* I think that the Boys will have a bigger gain in their results from Key Stage 2 too Key Stage 3 than the girls. I have Predicted this because the girls who come with high results from Junior School to High School do make an improvement but not better than the Boys in Our School. Where as the majority of boys come with normal and below average results and make a better improvement than the Girls. I think that this is because our school is an all Boys school, if it was a mixed school I do not think that the boys would have made a better improvement than the girls.
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