Intermediate Maths Driving Test Coursework

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GCSE Math’s Intermediate Coursework

Driving Test Coursework

This experiment has the aim of proving the hypotheses (that I shall develop) by handling data and managing it effectively to bring about realistic results. The hypotheses will be based upon test results from a driving school. I am intending to explore the success of males and females in a driving school. I shall do this by testing the number of one hour lessons and the number of errors in a random sample of 80 pupils. I aim to use this data to test several hypothesises.

Data: 

The data which I will be using in this investigation has been gathered from an unknown driving school. I am going to investigate in to have a look at the performance of this driving school. The raw data which I have been given is in list form and provides me with the performance of 240 students, of both sexes and includes:

  • The number of one hour lessons before successful test.
  • The total number of minor errors in test(s) taken.
  • The name of the instructor (4 different teachers).
  • The day of the test.
  • The time of the day of the test.

The data is in no particular order and reflects a large range and variety of results and performances. Here is an example of the data:

        

I have chosen to explore whether males are more successful than females or vice versa. I will break this line of enquiry down into three, manageable hypothesises. I will analyse whether the gender of the candidate affects the number of errors and whether the gender of the candidate affects the number of lessons required. I feel by investigating these three factors I will have enough evidence to give a clear answer to my investigation.

I am going to use the data given to follow my analysis and test the following hypothesises:

  • The more lessons you take, the less mistakes you will make
  • Males perform better than Females in the test
  • One gender performs better under because they get better instructors

Preliminary Analysis:

In order to notice investigate my hypothesises and notice patterns within this large amount of data, it is necessary to summarise and identify the 240 pupil’s data into diagrams and charts. To create these graphs, I had to sort the data, using excel, I used the auto filter feature in excel to highlight specific sections within the field which here was the number of pupils. So for my first graph, I sorted the data using the first field gender. This made easy for us to count the number of males and females so that we could create the graph.

By looking at the graph we notice that there is almost fifty- fifty split between the number of males and females doing the test. There is slightly more girls than boys but this is consistent with the male/female population ratio              today.

In this graph we notice that instructor B taught the majority of pupils (100) while instructor A taught 60 and C and D only taught 40 each.

In this graph we notice that Friday is the most popular day for pupils lessons as over sixty pupils attend at that day. The least popular day of the week is Tuesday at over thirty pupils.

Below are means and ranges of ‘Number of Lessons’ and ‘Number of Minor mistakes’, I did this as they are too complex to put in to a graph. I did not include ‘Time of day’ as its interpretation would become muddled.

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Selecting Sample:        

I will take a stratified sample to find 80 pupils. Sampling is necessary to attempt to give a general picture of all the data, there is too much data to deal with so I need a proportional section that reflects the whole. By using a stratified sample and using the mean and range, I can provide a fairly detailed answer to my hypothesises that will, in general, make full use of all the data. In order to reduce the danger of bias.

In order to select a sample from 240 into 80 ...

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