STAT 473 (Winter 2024)
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STAT 473 (Winter 2024)
Final Take-Home Examination
This final exam is due on April 19 (Friday) by 8:00pm at OnQ.
You must work on the exam independently.
Your work/report must reflect what you have learned in this course. Some extensions, explorations, and discussions may be included if relevant and offer further insights.
Please include a list of references if you have referred to books, articles, on-line resources.
Use of Chat GPT is not encouraged. If you do use Chat GPT, you must also reveal it as your reference; you are responsible to provide a description in an Appendix on what kind of help you obtained from Chat GPT and include the materials/answers you obtained.
Information in your reference list and Appendix will be used to assess the independence of your work for this exam.
Data Analysis and Report
Requirements:
• Analyze the data and write a concise but clear report. The suggested length is no more than 5 pages (text). Tables and/or figures should be inserted in the report (but do not count for length).
• Exploration of different models are encouraged. Present selected important results and evi- dence leading to your conclusions.
• Good scientific writing and clear explanation are highly valued. You can describe the data and variables; describe your initial exploration and the models you consider, includeselected results and figures for model fit, model assessment and comparison; and interpret your final model (or models) and explain what knowledge is achieved from your analysis in the appli- cation context.
• Your report should NOT include R code directly. Instead, include models, tables/figures and their descriptions in the report to present the important analysis and results. Submit your R code and raw output as a .R file at OnQ following your report, as evidence of your independent work.
• Please type your report.
Marking Scheme:
Total marks: 100;
60 marks on statistical analysis;
40 marks on report writing.
In a study of the relationship between car size and accident injuries, accidents were classified according to type of accident, severity of accident, and whether or not the driver was ejected. Table 1 gives a simpler version of the data, and Table 2 gives a more detailed version of the data from the same study. Find suitable models for the data in Table 1 and Table 2. Compare the models and analysis for Tables 1 and 2, draw conclusions for the study.
Table 1: The Car Accident Data: Version 1
|
Accident type Collision Rollover |
|||||
|
Car weight |
Driver ejected |
Severity |
Severity |
||
|
Not severe |
Severe |
Not severe |
Severe |
||
|
Small |
No Yes |
350 26 |
150 23 |
60 19 |
112 80 |
|
Standard |
No Yes |
1878 111 |
1022 161 |
148 22 |
404 265 |
Table 2: The Car Accident Data: Version 2
|
Accident type |
Accident severity |
Small |
Not ejected |
Small |
Ejected Compact |
Standard |
|
|
Compact |
Standard |
||||||
|
Collision |
Not severe |
95 |
166 |
1279 |
8 |
7 |
65 |
|
with |
Moderately severe |
31 |
34 |
506 |
2 |
5 |
51 |
|
vehicle |
Severe |
11 |
17 |
186 |
4 |
5 |
54 |
|
Collision |
Not severe |
34 |
55 |
599 |
5 |
6 |
46 |
|
with |
Moderately severe |
8 |
34 |
241 |
2 |
4 |
26 |
|
object |
Severe |
5 |
10 |
89 |
0 |
1 |
30 |
|
Rollover |
Not severe |
23 |
18 |
65 |
6 |
5 |
11 |
|
without |
Moderately severe |
22 |
17 |
118 |
18 |
9 |
68 |
|
collision |
Severe |
5 |
2 |
23 |
5 |
6 |
33 |
|
Other |
Not severe |
9 |
10 |
83 |
6 |
2 |
11 |
|
rollover |
Moderately severe Severe |
23 8 |
26 9 |
177 86 |
13 7 |
16 6 |
78 86 |
2024-04-06
Data Analysis and Report