QMS230: Statistics for Finance and Accounting R GROUP PROJECTWINTER 2021 DUE:April 11, 2021 by 11:59pm. MARKS: Total marks =25(or 10% of the final grade) PENALTY: There will be a 10% of the project -mark penalty for every day after the dueday (including weekends) that the project is late. Notes: 1. Nohandwrittenreportswill be considered for marking … Continue reading “Statistics for Finance and Accounting | My Assignment Tutor”
QMS230: Statistics for Finance and Accounting R GROUP PROJECTWINTER 2021 DUE:April 11, 2021 by 11:59pm. MARKS: Total marks =25(or 10% of the final grade) PENALTY: There will be a 10% of the project -mark penalty for every day after the dueday (including weekends) that the project is late. Notes: 1. Nohandwrittenreportswill be considered for marking purposes. 2. Submit one copy of the project report per group, R script file andindicateyourgroupnumberandthenamesandstudentnumbersofallthegroupmembers. Failure to indicate your group number will result in a zero grade. There will bepenalties for the inclusion of unnecessary. 3. Present your solution for Hypothesis testing according to the template shown inclass. All relevant R outputs must be included. 4. Upload your R script file together with your report online via D2L under Group Discussion. 5. ThereportmustbeasinglefileandinPDFformatonly.Failuretofollowthismayresultinazeromark. 6. Read this entire document. You will analyze dataset comes from arandom sample of the National Collision Database for 2017.This data was retrieved from the Government of Canada website. It includes all motor vehicle collisions in Canada on public roads in 2017 which have been reportedto the police. This data set contains a variety of data variables which are summarized in the datadictionary posted on the Government of Canada website. Source: Government of Canada. (2017).National Collision Database. Your data set was randomly resampled from a big data set that consist of more records. So,please be aware that each group will have its own data set. You will only focus on the relevantvariables and answer each question. Description of Data Variables: Variable Description Year Month 01-January up until 12-December Day of week 01-Monday up until 07-Sunday Collision hour 00-Midnight to 0:59 to 23-23:00 to 23:59 Collision severity 1–fatal or 2–non-fatal Number of vehiclesinvolved in collision Weather condition 1–clear and sunny, 2–cloudy, 3–raining, 4–snowing, 5–freezing rain, 6 –limited visibility, 7–strong wind Road surface 1–dry, 2–wet, 3–snow, 4–slush, 5–icy, 6–sand/gravel/dirt, 7–muddy, 8–oil, 9–flood Road alignment 1–straight and level, 2–straight with gradient, 3–curved and level, 4– curved with gradient, 5–top of hill, 6–bottom of hill Vehicle ID Vehicle typeSee Below Vehicle model year Person ID Person sex 01–Female, 02–Male Person age Person positionSee Below Medical treatmentrequired 1–no injury, 2–injury, 3–fatality Safety device used 01–none, 02–safety device used, 09–helmet worn, 10–reflectiveclothing worn, 11–helmet and reflective clothing, 12–other safety deviceused, 13–no safety device equipped Road user class 1–Motor Vehicle Driver, 2–Motor Vehicle Passenger, 3–Pedestrian, 4– Bicyclist, 5 – Motorcyclist Vehicle Type Code Description 01 Light Duty Vehicle (Passenger car, Passenger van, Light utility vehicles and light duty pick up trucks) 05 Panel/cargo van
