Mayfield High Statistics Coursework

Hypothesis

        I am going to investigate how your weight affects your lifestyle. This is my chosen investigation because I think it will be interesting to find out if your weight changes depending on which activities you undertake in your everyday life. I am going to first see if there is a difference in weights of males and females. Then find out if your favourite sport has an effect on your weight or not. Then I am going to find out whether the number of hours you spend watching T.V have an affect on your weight. And finally, I will find out whether the means of transport you use to get to and from school have an affect on your weight. But by looking into only weight, I will not be able to compare years as age affects weight, so instead I will be looking at their BMI (body mass index).

I am going to see whether:

• Your gender has an affect on your BMI

        I think that males weigh more then females because they stop growing at a later age the         females. Females go through puberty earlier then males and therefore stop growing         earlier then males. Therefore, I think that males will have higher BMI then females         who weigh less.

• Your favourite sport has an affect on your BMI

        I predict that the more active your favourite sport is, the less you weigh because you burn         more calories therefore less BMI.

Count of Forename

Year Group

Gender

7

8

9

10

11

Grand Total

Female

131

125

143

94

84

577

Male

151

145

117

106

84

603

Grand Total

282

270

260

200

168

1180

        I am going to be having a sample size of 10% of the total given population. This amount, I think, will give a representative number of pupils from each year and a representative number of males and females from each year. It is important for me to have a representative sample for the population so that my end results are not biased, so when I come to compare the results they are fair and correct.

Sample size =  1180× 10 = 118

                100

I will be using the stratified sampling method. To find my sample I will be using this formula:

No. of pupils in each year ×    sample size

       Total no. of pupils in all years

I will now find out how many pupils need to be chosen from each year using this formula.

Year 7 = 282 × 118 = 28.2 = 28

          1180

Year 8 = 270 × 118 = 27

          1180

Year 9 = 260 × 118 = 26

           1180

Year 10 = 200 × 118 = 20

            1180

Year 11 = 168 × 118 = 16

            1180

        I am now going to find out how many males and females need to be chosen from each year so that my chosen sample is representative of the males and females in each year.

- mean so that I can compare different averages, to see which BMI value is higher or lower                     between 2 sets of data

- Working out the mean will then help me work out the standard deviation. Standard deviation will show the spread and dispersion of my data. This again will just help me compare how similar the BMI’s are of 2 sets of data.

- Modal classes, this will show me which class of BMI contains the most number of pupils. I can see which modal class is higher and can then find out who has a higher BMI value, by comparing them.  

I am now going to start to investigate each of my hypotheses:

• Your gender has an affect on your BMI

I am going to be drawing cumulative frequency graphs, box and whisker diagrams, frequency polygons, and find the standard deviation, mean, mode and quartile ranges. I can then compare each of these graphs for males and females and see the variation and difference between the BMI’s.

These box and whisker diagram is for the males and females and shows their BMI range. The box and whisker diagram for males shows that the median value is closest to the upper quartile value, and therefore this data is negatively skewed. This means that most of the data is at the higher values, which shows that the males have a higher BMI. The box and whisker diagram for females. For this, the median is closest to the lower quartile value. This means that it is positively skewed, and most of the data is at the lower values, which means that the females BM values are low. This supports my predictions.