males and females driving

* 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. I have taken a random stratified sample to give me 30 males and 30 females which I will use to test my hypothesises throughout my investigation. Here is an example of the data:

Student

Gender of Student

Number of One-Hour Lessons before Successful Test

Total Number of Minor Errors in Test(s) Taken

Name of Instructor

Day of Test

Time of Day of Test

23

M

26

27

Drake

Thur

5

362

M

8

0

Drake

Fri

3

Performance: There are several factors which could affect the performance of drivers in general. These include:

* The teacher. The experience and teaching methods of the instructor.

* The weather conditions. Rain will restrict the performance while sunny weather will increase the ease of driving.

* The time of day. The time of day may affect the level of light and hence the visibility.

* The level of alcohol the candidate may have been consuming before his/hers test and lessons.

* The tiredness of the candidate.

* The age and physical attributes of the candidate. Pupils with better vision may find driving easier than others.

* The experience of drivers. One driver may have had more tests than others and therefore know the procedure. 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. For example, on Monday there could be stormy weather which will have a negative effect on the candidate while on Friday the sun could be shining which will make the test considerably easier.

* How the instructor affects the number of hours or the number of errors. To do this, I will have to take a stratified sample in order to make sure I have equal numbers of candidates for each instructor. I will need to have equal numbers of males and females in my sample and take the mean number of mistakes and compare and contrast this with the other instructors. I may also be able to take the mode, median, range, IQR and many other numerical measures. Whether the instructor affects the number of lessons required or the number of minor errors may be very useful in establishing which teachers are better and which are worse. This could help improve the quality of the driving school by enabling the worse teachers to be recognised and possible got rid off.

Line of Enquiry:

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

I am going to use the data given to follow my line of enquiry and test the following hypothesises:

* Do males make less minor errors than females?

* Do males require more one hour lessons than females?

Sampling:

I will take a stratified sample to find 30 random females and 30 random males. 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.