Stratified Sampling
When a population is made up of different groups, Bias can be reduced by representing each group in a sample. Our sample size is 10% of 1183, which is 118.
Stratified Sampling
Multiply 118 by the fraction, each sub-group represents of the whole population.
151/1183 X 118 = 15
131/1183 X 118 = 13
145/1183 X 118 = 14
125/1183 X118 = 12
143/1183 X 118 = 14
118/1183 X 118 = 12
94/1183 X 118 = 9
106/1183 X 118 = 11
86/1183 X 118 = 8
84/1183 X 118 = 11
YEAR 7 MALE (height & weight)
The correlation of height and weight in this graph of Year 7 male is weak.
YEAR 7 FEMALE (height & weight)
The correlation of height and weight in this graph of Year 7 Female is strong.
YEAR 8 MALE (height & weight)
The correlation of height and weight in this graph of Year 8 Male is not quiet strong.
YEAR 8 FEMALE (height & weight)
The correlation of height and weight in this graph of Year 8 Female is strong.
YEAR 9 MALE (height & weight)
The correlation of height and weight in this graph of Year 9 Male is strong.
YEAR 9 FEMALE (height & weight)
The correlation of height and weight in this graph of Year 9 Female is Weak.
YEAR 10 MALE (height & weight)
The correlation of height and weight in this graph of Year 10 Male is Weak.
YEAR 10 FEMALE (height & weight)
The correlation of height and weight in this graph of Year 10 Female is Weak.
YEAR 11 MALE (height & weight)
The correlation of height and weight in this graph of Year 11 Male is quiet Weak.
YEAR 11 FEMALE (height & weight)
The correlation of height and weight in this graph of Year 11 Female is quiet Weak.
ALL YEARS MALE & FEMALE (height & weight)
The correlation of height and weight in this graph of all the Years Male & Female is Very Strong.
Correlation Coefficient
My correlation coefficient is 0.525854261
The Main Study
My Hypothesis is that boys are taller and heavier then girls and the difference between boys and girls will increase as the students get older.
RANDOM SAMPLING
To make it fair and to avoid bias I choose to do random sampling. A quick way of doing this is to give each student a random number and then sort the data on this number which produces a random list.
I used the following steps to get my random samples:
- Type = RAND() in the first free cell to the right of the first line of the data and press ENTER to insert a random number.
- Click on this cell again and move the cursor to the bottom right of the cell until it changes to a black cross. Drag down until you reach the bottom of the data.
- To mix up the data, highlight the cell to the right of the first random number. Select the DATA menu and SORT. SORT BY COLUMN % and this will mix up all the data.
- Now select DATA menu and SORT and SORT BY YEAR GROUP THEN BY GENDER.
- Select the number of calculated students from each group and copy to a separate sheet.
Anomalies
To make sure my data is reliable I will test for anomalies to do this I will use the interquartile range and find out if there are any outliers
Year 7 Females
Height (Lower Quartile and Upper quartile)
Lq 1.03 Uq 1.54
Iqr 0.51
The outliers are 1.03 and 1.54 but there are no anomalies in this data
Weight (Lower and Upper quartile)
Lq 40 Uq 70
Iqr 30
The outliers are 26.875 and 61.875 but there are no anomalies is the data
Year 7 Males
Height (Lower Quartile and Upper Quartile)
Lq 147 Uq 159.5
Iqr 12.5
The outliers are 134.5 and 172
Weight
Lq 39.5 Uq 49.5
Iqr 12.5
The outliers are 29.5 and 59.5
Year 8 Females
Height (Lower Quartile and Upper quartile)
Lq 155 Uq 163
Iqr 8
The outliers are 145 and 173
Weight (Lower and Upper quartile)
Lq 45 Uq 52
Iqr 7
The outliers are 36.25 and 60.75
Year 8 Males
Height (Lower Quartile and Upper Quartile)
Lq 152 Uq 162
Iqr 15
The outliers are 133.25 and 185.75
Weight
Lq 38 Uq 52
Iqr 14
The outliers are 20.5 and 69.5
Year 9 Females
Height (Lower Quartile and Upper quartile)
Lq 153 Uq 162
Iqr 9
The outliers are 141.75 and 173.25
Weight (Lower and Upper quartile)
Lq 45.25 Uq 52
Iqr 6.25
The outliers are 36.8125 and 60.4375
Year 9 Males
Height (Lower Quartile and Upper quartile)
Lq 154.25 Uq 172.5
Iqr 18.25
The outliers are 131. 4375 and 195.3126 but there are no anomalies in this data
Weight (Lower and Upper quartile)
Lq 45.5 Uq 60
Iqr 14.5
The outliers are 27.375 and 78.125 but there are no anomalies in this data
