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maths data handling

Extracts from this document...

Introduction

Introduction: I have been given a data set containing 240 data items containing information relating to driving tests. My aim is to investigate what factors influence a successful outcome from different fields contained in the data sheet: * Gender of the Driver * Number of 1hr lessons * Number of minor of mistakes * The driving instructor Most of the fields shall be investigated to see if there is any pattern connected with successful drivers apart from. * The Day and Time the test was taken out Initial Analysis: The Initial Analysis of the entire data set shows that there is: * 116 Male drivers. * 124-Females > 60 Learners for Instructor A > 100 Learners for Instructor B > 40 Learners for Instructor C > 40 Learners for Instructor D The Mean number of: * Minor mistakes are 16.78 * 1Hour Lessons is 23.03 Hypothesis One: For this data set Men on average made fewer minor mistakes than women in their driving test. Planning: In order to investigate this hypothesis I will take a random sample of 30 male drivers and 30 female drivers. And compare the number of minor mistakes they made in their driving test. To make this comparison I will construct box and whisker diagrams. ...read more.

Middle

I know this as the gradient was much steeper and the correlation coefficient was more negative than any other of the scatter graphs. What may have influenced the box and whisker diagrams to have different results than my scatter graphs may have been that each sample was of different size. Instructors A had 30 drivers and B had 50 drivers whilst Instructor C + D had only 20 drivers meaning these instructors had less chance of either failing drivers than Instructor's A + B would have. Hypothesis 5: In this Data Set, some Instructors do better/worse with the other Gender. Planning: This shall be my final Hypothesis, so I intend to make a reliable investigation- by taking a sample of 15 Males and 15 Females from each Instructor in the field of "minor mistakes" and creating Box and Whisker Diagrams with these samples. Once this has been done I will use the samples again and create Scatter Graphs for each. Examining the Number of Lessons each driver took against the number of Mistakes they made for each instructor and writing an analysis of each below them. Statistics box: Female Samples Instructor's Data Statistics A B C D Lower Quartile 5 10 5 13 Median 11 19 11 25 Upper Quartile 14 23 14 28 Mean 9.86 17 9.86 21.86 Range 18 30 18 31 Inter ...read more.

Conclusion

Then whenever I calculate how many males and females have passed I can take that number and use it and the total number who took the test and work out the probability in which males and females have of passing with each instructor as a whole and then I can find the probabilities that males and females will pass with each instructor. So here as follows are the probabilities of Drivers Passing there test with each Instructor from both Genders. Male Probability of Passing their Driving Test Instructor No. of Pupils who passed No. of Pupils who Failed Total no. of Pupils Chance of passing A 21 8 29 72.41% B 25 24 49 51.02% C 9 9 18 50% D 5 15 19 26.32% Female Probability of Passing their Driving Test Instructor No. of Pupils who passed No. of Pupils who Failed Total no. of Pupils Chance of passing A 22 9 31 70.97 B 14 37 51 27.45% C 8 14 22 36.36% D 1 19 20 5.00% Over all Chance of Passing their Driving Test Instructor No. of Pupils who passed No. of Pupils who Failed Total no. of Pupils Chance of passing A 43 17 60 71.60% B 39 61 100 39.00% C 17 23 40 42.50% D 6 34 40 15.00% ?? ?? ?? ?? Handling Data: Driving Tests ...read more.

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