MDM4U Culminating Project –Example

Outline an action plan for investigating the relationship between driver age and number of accidents.

  1. Hypothesis
  • the graduated license system in Ontario has resulted in a dramatic decrease in the number of accidents involving teenage drivers
  1. Data Collection
  • analyze the data in the table below:

Vehicle Collisions in Ontario
Age / Licensed Drivers / Number in Collisions / % of Drivers in Age Group in Collision
16 / 85,050 / 1,725 / 2.0
17 / 105,076 / 7,641 / 7.3
18 / 114,056 / 9,359 / 8.2
19 / 122,461 / 9,524 / 7.8
20 / 123,677 / 9,320 / 7.5
21-24 / 519,131 / 36,024 / 6.9
25-34 / 1,576,673 / 90,101 / 5.7
35-44 / 1,895,323 / 90,813 / 4.8
45-54 / 1,475,588 / 60,576 / 4.1
55-64 / 907,235 / 31,660 / 3.5
65-74 / 639,463 / 17,598 / 2.8
75 & older / 354,581 / 9,732 / 2.7
Total / 7,918,314 / 374,073 / 4.7 (average)
  • the data in the table is a starting point, however, it is only data for one year
  • one would need accident data for other years including the years before and after the introduction of graduate licensing
  • one would need the data separated by age and even by gender or by region
  • one would need to consider other variables such as driving for pleasure or work, accidents by time of day, accidents involving impaired drivers, accidents by type of vehicle, and so on.
  1. Data Organization
  • the data should be organized to allow one to test your hypothesis; this means that one would need to isolate the effects of the graduated license system from other factors such as population that may have changed over the years you are examining
  1. Data Presentation
  • when presenting the data, one would need to keep in mind that the data will bepresented in a written report and in a class presentation
  • use bar graphs, circle graphs, line graphs or tables to present the data
  • choose ways of presenting the data that help address the hypothesis; this does notmean distorting the data by using inappropriate scales or ignoring outliers and data that does not support your hypothesis
  • you are testing the validity of your hypothesis, not trying to convince your audience ofthe correctness of your claim
  1. Data Analysis
  • use the tools you have learned in this course to analyse your data
  • summary statistics, measure of dispersion, analysis of outliers, regression, and other techniques may be appropriate
  • it may be possible to perform a formal hypothesis test on your data
  • you should be able to relate your results to probability theory and probabilitydistributions, where appropriate
  • you may be able to use a simulation to test your results
  • the choice of analysis tools will depend on the hypothesis that you are testing