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# males and females driving

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Introduction

Thomas Lock 10Z Maths GCSE Data Handling Coursework Summer 2005 "Do males perform better than females at the driving school?" Scenario: I am a business consultant brought in to have a look at the performance of a driving school. I have been given the raw data which shows, in no particular order, how different students have got on in their driving tests. Introduction: This experiment has the aim of proving the hypotheses (that I shall develop) by handling data and managing it effectively to instigate 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 30 males and 30 females. 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 acting as a business consultant brought in to have a look at the performance of said driving school. ...read more.

Middle

Also, the number of lessons will affect the ability of the candidate. The difference in performance between males and females may be affected by the following factors: * Females may perform better than males because it is widely believed they have a larger concentration span. * Males may be more confident at the wheel and therefore be less prone to make mistakes. Possible Lines of Enquiry: I am the business consultant and there were several lines of enquiry that were open to discussion. I could have, for example, chosen to investigate the following: * How the day of the week and time of the test affects the number of errors . In order to investigate this hypothesises, I would have to take a sample of equal numbers of males and females for each day of the week. I would have to take into account that the day of the week may not affect the result but I will have to take the mean number of errors for each day and compare and contrast the results. This may be unreliable as the weather conditions may randomly vary during the week, hence affecting the number of errors. ...read more.

Conclusion

Sampling is necessary to attempt to give a general picture of all the data. By using a stratified sample and using the mean, median, range and mode, 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, I am going to be taking the instructor into account when doing my stratified sample. For example, my 30 females may have all been taught by Drake and my 30 males may have all been taught by Bell which may have directly affected the performance of the different sexes. In order to prevent this happening, I am going to make my stratified sample so that they proportion of pupils being taught by the different instructors in the whole data will be equal to the proportions of pupils being taught by the instructors in my sample. To do this, I will count up the number of males being taught by each instructor and divide the total number of males by this number. This will give me the number of males being taught by that instructor that I need to include in my sample. I will repeat this for each instructor and also for the females. ?? ?? ?? ?? ...read more.

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