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For this investigation I have four hypotheses, which are: 1) There is a strong positive correlation between arm-span and height in both males and females. I have based this on the Vitruvian theory. 2) Females are generally shorter than males.

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Introduction

Pupil Data Introduction In this Investigation I will investigate the different variables of data of 100 males and 80 females. This data is secondary data as I did not collect it myself, but I will trust it to be accurate because it was given to me by my teacher. The data I will be working with is numerical data, as it is quantative. This data is not qualitative (non-numerical data). Numerical data is always discrete or continuous. Discrete data is data that cannot be changed. Examples of this in the data I am using are date of birth, left-handed, can roll tongue, etc. Continuous data is dat that changes overtime. Examples of this in the data I am using are shoe size, height, weight, arm-span, etc. My Hypothesis For this investigation I have four hypotheses, which are: 1) There is a strong positive correlation between arm-span and height in both males and females. I have based this on the Vitruvian theory. 2) Females are generally shorter than males. I have based this hypothesis on my observations. 3) The weight of males is more spread out than females. I have also based this hypothesis on my own observations. Sampling To investigate my hypotheses I will need to sample the data of 100 males and 80 females. I am sampling them to ensure my data is unbiased and representative of the whole school. Stratisfied Sampling The method that I will use to sample is stratisfied sampling. I have chosen this method as it is most suitable to use, because the male and female populations are not the same size in the data I have been supplied with. This method also helps ensure that there are a fair proportion of samples from each group of population. To do stratisfied sampling you will need to divide the population into categories (strata) i.e. age and gender. My strata is gender. ...read more.

Middle

0 0 20/03/68 0 0 5 168 58 156 15 54 47 022 0 1 09/02/68 1 1 3.5 155 55 152 20 55 45 040 0 1 23/01/68 1 1 4 161 60 154 17 53 47 052 0 0 13/09/67 1 1 7 169 60 170 19 56 60 007 1 0 11/11/67 1 1 4 161 64 156 19 56 52 017 0 0 09/06/68 1 1 7 164 60 166 17 53 52 078 0 0 23/11/67 1 1 7 166 70 169 20 56 59 012 0 0 18/06/68 1 1 5 162 67 163 19 56 55 048 0 0 03/11/67 1 0 4.5 160 60 160 15 57 54 042 1 0 13/10/67 0 1 4 162 59 157 17 56 50 013 0 1 24/04/68 1 0 5 163 65 160 18 54 42 062 0 0 28/06/68 1 0 5.5 161 59 163 17 53 49 077 0 0 18/10/67 1 1 4 155 57 154 20 55 43 033 0 0 23/12/67 1 1 7 170 66 173 21 57 55 059 0 0 10/01/68 1 1 5 158 70 152 17 56 56 015 0 0 03/10/67 1 1 4.5 159 61 151 15 56 53 To prove my hypothesis 1: I will draw 2 scatter diagrams with one axes for arm span and the other for height. I am drawing 2 so I can check if my hypothesis is correct in females as well as males. If my hypothesis is correct there should be a very strong positive correlation between height and arm span for males and females. I will also compare their product moment correlation coefficient, r, as this form of measure does not depend on scale of axis on the scatter diagrams or the size of my sample. I will use Spearman's rank correlation to see if there is an agreement between arm span and height in male and females. ...read more.

Conclusion

x 45 45 47 52 53 55 57 60 62 62 65 (x-)� 96.4324 96.4324 61.1524 7.9524 3.3124 0.0324 4.7524 26.8324 51.5524 51.5524 103.6324 I now have to add up all the results which make 503.6364. I now have to divide this by the number of values which is 11. 503.6364 divided by 11 makes 45.78512727. I then have to square root it which makes 6.766471. This is the standard deviation for males. I have worked it out for males by myself to show you how it is done but for the females I am going to use excel to work out the standard deviation to save time. Standard Deviation for females I am now going to work out the standard deviation for females on excel. The standard deviation for females is 4.853407. The standard deviation also proves my theory because the male's standard deviation is bigger than the female's standard deviation. This means my theory, of males weight is more spread out than females, is true. Conclusion In my coursework I have proved all my theories except for the second half of the 1st hypothesis, which was there is a strong positive correlation between arm span and height in females. In males my hypothesis was correct but not in females. This might have been because I collected sample data for some females who had a big difference between in arm span and height. In the data I was given I had found another error. The data I was given was for a school year, so all the children should have either been born in 1967 or 1968 but one of the people in the data was born in 1938. He's reference number is 051. I did not have him in my sample data. If there was one mistake in this data there could have been more that I don't know about. These might have affected my results. Overall I don't really think my results have been affected and I am pleased with what I have got. Some other things that could have affected my hypothesis are: * 1 ...read more.

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