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GCSE: Height and Weight of Pupils and other Mayfield High School investigations
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I think a third of the data will represent my hypothesis well. To collect the data I will use systematic sampling rather than stratified or random sampling. Systematic sampling is the method used to produce a sample from a population. I will use systematic sampling by choosing every fifth person of each gender at regular intervals. I am choosing to use systematic sampling because it's easy to use and it avoids the confusion of perhaps choosing the same number twice when using random sampling.
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Mayfield High. I will set about carrying out various test in order to come up with a seeming solution to my prior hypothesis. Hypothesis: Boys are academically better than girls.
4 5 4 4.333333333 78 3 3 3 3 83 3 3 4 3.333333333 108 4 4 4 4 112 3 4 4 3.666666667 109 5 5 5 5 100 4 4 4 4 116 6 6 6 6 100 4 4 4 4 78 2 3 2 2.333333333 86 2 3 4 3 91 3 3 3 3 107 5 5 5 5 110 4 5 5 4.666666667 90 3 3 3 3 102 4 4 4 4 102 4 4 4 4 101 4 4 4 4 100 4 4 4 4 103 4 4 4 4 112
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Mayfield High. I have decided to make my hypothesis: The distance a student lives from the school determines they method of travel they use to get to school.
Then I combined my results from KS3 and KS4 for each type of travel. I will be using cumulative frequency, this will help me get the lower quartile, upper quartile, inter-quartile range and median. Then I will be able to use this information to create box plots. The box plots will help me to compare my data. I will also be using standard deviation. Standard deviation is a method used to find out the variation of a sample. This will help me find out which type of travel has the most spread out data and which does not.
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First I will put my data into a table so it's easier for me to find the mode, mean, median and ect. So I can interpret and understand the data more clearly, another way of to compare the data is to draw a dual bar chart and a scatter graph so I can compare and look if there is any pattern or correlation. As you can see I created a table for my data which I will use to create a dual bar chart, scatter graph and a cumulative frequencey chart.
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] SD: Mean: of grouped data: = individual data = number of values = frequency Normal Distribution: 1. To see whether the first hypothesis is true, I will separate each gender from each Year group and then plot the data in a Box and Whisker Plot. I will take a sample of 50 pieces of data from each Year so that the amount of data will be equal. To find out how many pieces of data I will take from each gender, I will use stratified sampling and use a random number generator to select the exact entries.
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For the second part, I will then choose 5 more boys and 5 more girls from the remaining data's to go along with the 5 boys and 5 girls I already have. In both part of the pre - test, I will find the mean of all the data's and then draw a scatter graph with a line of best fit drawn on it. Full Test In the proper full investigation where I will be investigation all the 30 boys and 30 girls data's, I will find the mean, median and range of all the data's.
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Source of information I'll collect the information from the Mayfield High School booklet available on the official website which has all the data in an Excel spreadsheet format. Reasons for choosing source of information The main reason why I choose to look at Mayfield High School is because; the data within the booklet is accurate as it is the results of carefully prepared and planned tests, so therefore the results will be very accurate. Also, as the information are based on examinations enforced by the government - the results are more likely to be reliable than that of class tests.
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Gender makes no difference to IQ. Hypothesis 3: Key stage 2 results are not influenced by gender. The data I have is secondary, collected by a school I do not know so I am not sure if this data is reliable or not. I am not going to use any obvious anomalous data. Hypothesis 1 I am going to take a stratified sample of the whole school to find out if there is a strong positive correlation between IQ and Key Stage 2 results.
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Random sampling is a sampling technique where we select a group of subjects (a sample) for study from a larger group (a population). Each individual is chosen entirely by chance and each member of the population has a known, but possibly non-equal, chance of being included in the sample. Stratified sampling To carry out my Stratified sampling, I used the following method. In this case, the size of the population is 1183 whilst the size of the sample is 50 Year 7 Boys 151 ----- X 50 = 6 1183 Year 8 boys 145 1183 x 50 =6 Year 9
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However, the local papers might only have news about the sports from the town or city that that newspaper is written for. For example, the 'Stourbridge News' will only have news about sport taking place in Stourbridge. I have done a pilot study to find out how accurate my hypotheses are. In the pilot I have found out the following pieces of information: - * An average for how many words are in a sentence in each paper. * The cost of each paper.
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and GCSE maths (%) simply to show me the mode. To display my data properly I will use a frequency polygon. I then will go on to do a stem and leaf diagram comparing the Attendence (%) and GCSE maths (%) of students to find out the median. After I have done this I will plot my data Attendence (%) and GCSE maths (%) onto a scatter grapgh. Using the line of best fit I will look for a correlation to show me the relationship between the Attendence (%)
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The aim of my investigation is to find out if the following hypothesis is true: Girls have a higher IQ than boys.
All the other information is irrelevant. To get my sample I am going to use a calculator. I will press the 2ndf button then the number 7 then 0 and =. This will bring up a random nimbeer on the calculator e.g 0.233. I will sort the data into two separate lists, one for boys and one for girls. I am goin to start at girl number 1.
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which I have rounded up to 120. Through my chosen sample size of 10% which I carried out on each year group for both boys and girls I found that some of the numbers were not whole. In order to make these numbers whole I rounded down on all data I was presented with. As I was rounding down my sample of all student no longer was 120 but 114. I will do this by finding the number of boys or girls in a certain year group. I then divided that number by the total students at 'Mayfield High School'.
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Diagrams: I had to make sure the rule worked so I double checked by using 3-D cubes to see whether the rule was 100% correct. The sheet shows this as an example. It is a line of five cubes and it has 30 faces and 13 of the faces are hidden. I tried changing the amount of cubes, to see what results I Got. I used 7 cubes and noticed that I now had 42 faces and 19 of the faces are hidden.
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The next step once you have found the population of males and females would be to divide that population by the total population which would give a product which could then be divided by the number of samples you are working with; this will give you the stratified amount of samples you should work with. I am ideally looking to sample 30 people from each year group and I will use stratified sampling to find out how many boys and girls from each year to produce a fair investigation.
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There are a number of details on the secondary data sheet for each students e.g. Name, Age, year group, height and weight. I'm going to use this secondary data to investigate the hypothesis: "Boys in KS4 are heavier than girls in KS4" There are too many pupils to employ all the results so I'll use a sample of the boys and a sample of the girls. In order to make comparison easier I will use the same number of boys as girls in my two samples.
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Once I have done this I will show my data onto a bar graph comparing the Attendence (%) and GCSE maths (%) simply to show me the mode. To display my data properly I will use a frequency polygon. I then will go on to do a stem and leaf diagram comparing the Attendence (%) and GCSE maths (%) of students to find out the median. After I have done this I will plot my data Attendence (%) and GCSE maths (%) onto a scatter grapgh. Using the line of best fit I will look for a correlation to show me the relationship between the Attendence (%)
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From graph 1 we can see that there is a positive correlation between the IQ results and students' total key stage 2 results. The graph suggests that if a person has a higher IQ their total key stage 2 results will be higher; this is what I had to show for this hypothesis. Graph 1 show a sample of just 50 students randomly selected, so I could extend the sample which may make it more accurate or repeat it with different students to back up the result.
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These are quite clearly inaccurate. I therefore fear some of the other data may have been inaccurately entered into the database. However, it is impossible to tell in the case of most of the other columns and therefore, I must simply resolve to just look out for any abnormalities in my calculations or diagrams that may be accounted to inaccurate data in the database. After generating 30 random numbers, I now have the set of data shown in Appendix A at the rear of this project to base my investigation on.
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Guesstiamte - investigating whether men or women between the ages of 15-25 are better at guessing the length of a line and the size of an angle.
.......................cm In degrees please guesstimate the size of the angle ..........................degrees The questionnaire is to the point, gathers all the information it needs and is not intrusive. Random questions are not needed for this investigation. The actual size of the angle is 38� and the actual length of the line is 4.5cm. Sample. 81 people answered my questionnaire; 49 males and 32 females. I used 30 of these people as any less would be insignificant. To make it a fair investigation I took a stratified sample.
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48 8 Female 1.62 46 8 Female 1.56 54 8 Female 1.52 58 8 Female 1.57 45 8 Female 1.60 57 8 Female 1.59 44 8 Female 1.58 52 8 Female 1.59 50 8 Female 1.55 42 8 Male 1.72 57 8 Male 1.52 43 8 Male 1.48 40 8 Male 1.72 50 8 Male 1.50 50 8 Male 1.62 38 8 Male 1.48 26 8 Male 1.74 45 8 Male 1.77 54 8 Male 1.73 56 8 Male 1.55 43 8 Male 1.45 72 8 Male 1.52 45 8 Male 2.00 35 9 Female 1.65 48 9 Female 1.6
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Both numbers of the product are even. I got this by dividing the main number by 2 and then multiplying it by itself again to get maxi product. Number Product 16,0 16x0=0 15,1 15x1=15 14,2 4x2=8 13,3 13x3=39 12,4 12x4=48 16 12.5,3.5 12.5x3.5=43.75 11,5 11x5=55 11.5,4.5 11.5x4.5=51.75 10,6 10x6=60 10.5,5.5 10.5 x5.5=57.75 9,7 9x7=63 9.5,6.5 9.5x6.5=61.75 8,8 8x8=64 8.5,7.5 8.5x7.5=63.75 7,9 7x9=63 I have stopped my table because the answers of the product are now starting to be repeated.
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Random Sample This is my random sample of boys and girls of Mayfield High School. I separated them into boys and girls so it is easier to analyse the data. GIRLS BOYS Year Height (m) Weight (kg) Year Height (m) Weight (kg) 7 1.61 47 7 1.47 41 7 1.50 45 7 1.64 50 7 1.72 53 7 1.36 45 7 1.46 40 7 1.71 49 7 1.48 47 7 1.65 64 7 1.62 65 7 1.51 59 7 1.43 38 7 1.60 43 7 1.56 43 7 1.62 47 8 1.60 50 7 1.51 39 8 1.59 52 8 1.70 49 8 1.62 51 8 1.56 59 8 1.50 45 8 1.52 45 8
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My next step will then be to investigate further; checking whether different sized grids affects the results and the pattern we obtain. If this occurs, I will then have to find a different pattern or relation connecting T-Number, T-Shape and grid size. 4. I will then try other transformations and combinations of translations; investigating the relationship between the T-Total, the T-Number and the translations. 5. The last step will be to determine a formula which takes into account transformations and different grid sizes.
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I will do this by adding random number on the data's end. For example it display 0.17 so I will use it as 17 then I go down to data 17 and take that data to a new paper. For Year 7 boys I have to collect six random samples therefore, I will repeat this process 6 times. I will do same thing for different years of girls and boys. The Reasons The reason why I use stratified sampling is because that I can find the answer more accurate, because that can even give me the ratio of the school
- Word count: 2782