Relationship Between Weight and Height

My School is a secondary school and is of mixed genders from ages 11 to 17 plus a 6th from which has students of 17-19years. The school is based in the country side near to several small towns and villages, most of the students around the area come to this school. Preliminary Investigation I have decided to investigate the following fields; Weight and Height. I have decided upon these two values because I am curious if there is any connection between them, as I know many people my age which are around my weight but which are a lot shorter than me. The fields I have chosen to investigate are both forms of continuous data, in contrast to data that is known as discreet, for example, Gender or Favourite sport. Discrete data usually occurs in a case where there are only a certain number of values, or when we are counting something (using whole numbers). Continuous data makes up the rest of numerical data. This is a type of data that is usually associated with some sort of physical measurement, in this case, height and weight.
Data is discrete if there are only a infinite number of values possible or if there is a space on the number line between each 2 possible values. Discrete data usually occurs in a case where there are only a certain number of values, or when we are counting something (using whole numbers), and so this form of data does not provide much scope when concerned with comparability and analytical values. Therefore I have chosen to investigate a type of data I will be able to conclude un-limiting numerical data from as so I can make detailed analogies and conclusions. I predict that there will be a correlation between weight and height as when you grow taller, your body mass increases as you have more bone etc to make up your body. However it would be interesting to find out is if you compare people of different ages weights when their height is the same, and body maturity may make the person heavier due to developed muscles etc. Also it may be intriguing to discover the relationship between males and females of the same age. Within my investigation I am concerned with gender difference as upon examination of my data it is apparent that values for each sex are of poles apart, in that values for males are of higher value and lower for females, I believe this will become more apparent as my investigate proceeds. Within my preliminary investigation I will be analysing a sample of random subjects, these subjects will be chosen methodically by obtaining a range of thirty numbers from the range of each boys and girls. Year Group Number of Boys Boys to be surveyed Number of Girls Girls to be surveyed Total Total of Students surveyed 7 151 8 131 7 282 15 8 145 7 125 6 270 13 9 118 6 143 7 261 13 10 106 5 94 5 200 10 11 84 4 86 5 170 9 Total 604 30 579 30 1183 60 I have chosen to take a sample of 30 boys and girls as I have calculated that 30 out of the total number of each gender produces a result of about 5%, which I consider a good starting point for my pre-test as it will produce quick, obtainable data and will give me a good idea of how I can deal with the information as so I can improve my testing further, for a more detailed analysis later on. Percentage sample of boys =30/604 × 100 =4.9669% Percentage sample of girls =30/579 × 100 =5.1813 I used Quota sampling to collect my data by simply choosing students walking past me from the corresponding gender and year groups. This may not be the fairest way of obtaining my data but I believe that is was just as random as it would be if I had catalogued every single student and picked them out at random. I used this method to generate a sample of 30 boys and girls: Girls Sample Number Year Height (m) Weight (Kg) 1 7 1.62 40 2 7 1.32 35 3 7 1.62 49 4 7 1.49 53 5 7 1.65 43 6 7 1.62 65 7 7 1.60 47 8 7 1.52 33 9 8 1.72 43 10 8 1.60 44 11 8 1.60 42 12 8 1.61 46 13 8 1.70 53 14 8 1.76 50 15 8 1.58 72 16 8 1.59 55 17 9 1.53 52 18 9 1.78 59 19 9 1.71 42 20 9 1.62 45 21 9 1.69 48 22 9 1.51 65 23 9 1.58 55 24 10 1.70 50 25 10 1.80 60 26 11 1.73 64 27 11 1.72 51 28 11 1.73 48 29 11 1.65 54 30 11 1.71 42 Boys Sample Number Year Height (m) Weight (Kg) 1 7 1.45 40 2 7 1.42 48 3 7 1.44 42 4 7 1.49 47 5 7 1.53 35 6 7 1.49 67 7 7 1.74 70 8 7 1.52 54 9 8 1.45 72 10 8 1.50 39 11 8 1.72 46 12 9 1.67 52 13 8 1.72 57 14 8 1.62 52 15 9 1.60 60 16 9 1.62 40 17 9 1.53 45 18 9 1.60 40 19 9 1.64 65 20 10 1.75 45 21 10 1.66 70 22 10 1.77 57 23 10 1.63 56 24 10 1.87 70 25 11 1.57 60 26 11 1.75 60 27 11 1.96 93 28 11 1.74 50 29 11 1.62 92 30 11 1.70 72 Handling the Data I also examined accuracy of the data, as I can verify the truthfulness of my data I will examine it on face value, I have ignored any data that falls outside of 2 decimal places, weights that are not within the parameters 30-100kg and heights outside 1-2 metres. I have decided to eliminate these values as I consider them to be abnormal and biased, I can conclude this by examining bmi, as I am aware that any-one with a body mass Index lower than 18 or higher than 35 is not typical. This applies for height as upon examining heights of my class mates it is apparent that standard height is not blow 1m or above 2m. Obtaining evidence for analysis My analysis will concern the differentiation of boys against girls, as I am aware, from the age of 11 it is apparent both genders take on a from of change and depending on their personal chemistry a change in weight and height is one of the major factors within adolescence. By obtaining data that I can tabulate I can carry out a series of comparisons and conclude conclusions concerning my applied data. There are a range of statistical calculations I can make use of. I am aware I can obtain the following, for both genders and both height and weight:
Frequency distribution
Mean;
Mean deviation;
Standard deviation;
Median;
Range;
Inter-quartile range;
Central tendency;
Measure of dispersion or spread;
Distribution.