|
|
This is only a preview of the paper
Click here to register and get the full text.
Existing members click here to login
|
|
|
This is an extension to the previous line of enquiry, which includes additional data, which was omitted from the first hypothesis due to the limited results. ...
Data:
The data I will be analysing is secondary data that my course lecturer has provided. ... Both types of data, height and weight are quantitive and continuous. ... (eg 180 / 4 = 45)
Ungrouped data
Using the data on the next page I will plot a scatter diagram, which will demonstrate the relationship, if any, between the heights and weights recorded. This will be carried out for both genders and I will then add a line of best fit that will show the trend of the data in a positive or negative correlation.
Ungrouped data girls
Gender Height (m) Weight (kg)
Female 1. ... 73 64
Ungrouped data boys
Gender Height (m) Weight (kg)
Male 1. ...
Line of best fit and equation
The diagram has proved that there is an increase in weight in relation to an increase in height thus indicating a positive correlation in the data. ...
These lower values have been excluded from all other graphs in this report as they have no relevance to the sample data as there were no students under 1. ...
Gender divide
I will now divide the genders in order to establish whether the correlation is better, or no better, when the data is separated. ... 5
From this ungrouped data it can be seen that on average boys are taller and weigh more than girls.
Grouped data
Height, all pupils
Here I have separated the height data into groups of 2cm bands and then grouped the weights into 2Kg bands also. ... 00 76<78 0 99
78<80 0 99
80<82 1 100
Data Analysis
I will now display this data using a cumulative frequency diagram plotting the grouped data for both height and weight against frequency.
Approximate Word count = 1355
Approximate Pages = 5.4
(250 words per page double spaced)
|
|
|
|
|
|