Statistics
Introduction:
In this investigation, I will investigate whether the more hours of TV watched the greater your IQ. My results came from secondary data from Mayfield. It consists of various different information such as height and weight of 813 students in both KS3 and KS4. It does not matter that the data is secondary as it is still accurate. I will randomly sample 30 people and collect this information through secondary data. To random sample you type into your calculator RAN# (amount of results -1). On the Mayfield data excel page each row corresponds with a number. Each time a new number comes up you record the number you received. If you get the same number twice, you move onto the next number. If data is missing, you move onto the next number. When you receive 30 data for each variable you stop sampling. My data was very limited as I only had a sample of 30. This is because the bigger the sample, the more accurate my results. I could improve my results by repeating the investigation to come to a solid conclusion. This will enable me to come to a conclusion to whether the amount of hours TV watched will affect your IQ level. With this data I can draw a scatter diagram and spearman’s ranking to determine whether the correlation is positive or negative.
Hypothesis:
My hypothesis is ‘the more hours of TV watched, the greater the IQ and therefore predict that there will be a strong positive correlation. This is because television is known to be insightful and full of thought provoking content. TV is also highly informative, educational, therefore stimulates the brain. Moreover, television is the most powerful mediums of communication that can not only improve a person’s IQ but help people interact with one another. To investigate this hypothesis I am going to plot a scatter graph of the amount of hours TV watched against a person’s IQ and draw a line of best fit. This will tell me if there is a positive or negative correlation. I hope to prove this hypothesis in my investigation.
Data-handling:
If I was to be doing comparison, I would find the mode, median and mean for each variable and draw a box-plot. However, I am doing relationship so with this data I can plot my results onto a scatter diagram and determine whether the correlation is positive or negative. I will also be using spearman’s ranking to check whether the correlation is correct. During this investigation I did not encounter any problems as I calculated my results to the upmost accuracy.

Spearman’s ranking:
You can do spearman's rank by first stating your hypothesis, ranking both sets of data in descending order and getting the difference between the sets. Square this value, add them all up and then use the formula where n is the number of ranks. My spearman’s rank shows a strong positive correlation as my result is closer to 1. If my result is smaller than 0.5 it is negative correlation whereas if my result is closer to 1 it is a stronger positive correlation. However, my answer was 0.94 which shows that the correlation not only is positive but strong positive. This means as the amount of hours watched gets larger, the IQ gets larger to.
Scatter graph:
A scatter plot is a statistical graph showing the relationship between two variables. One variable is shown on the horizontal (X) axis, and the other on the vertical (Y) axis. Each subject is plotted with a point that corresponds to that subject's X and Y scores. For example: IQ and amount of hours TV watched. My scatter graph shows that there is a strong positive correlation between the amount of hours TV watched and the IQ level. This means that the more hours TV watched the higher the IQ which supports my hypothesis. All my working out and results were accurate so my conclusion and the outcome of this investigation is reliable.

Spearman’s ranking:
TV
RTV
IQ
RIQ
D
D
15
11
101
5
6
36
10
8
102
6
2
4
6
5.5
102
6
-0.5
-1
42
22