2021/12/1 下午3:14 Project overview: STA130H1 F 20219:An Introduction to Statistical Reasoning and Data Science
https://q.utoronto.ca/courses/235890/pages/project-overview 1/5
Project overview
Highlights (more info and links below)
Both the task and marking rubric are the same, whether you work in a group or not. Make
the best choice for your own work style, availability, and development goals.
You can work individually or in a group of 2, 3, or 4 students, total. Groups will need to
complete a group work agreement and register by Tuesday, Nov 23 at 11:59 a.m. ET.
(Extension provided to Nov 26 at 11:59 a.m. ET.)
You can pull the project template and data through this link
(https://jupyter.utoronto.ca/hub/user-redirect/git-pull?
repo=https%3A%2F%2Fgithub.com%2FUofT-sta130%2FSTA130-F21-final-project-
template&urlpath=rstudio%2F&branch=main) , it will create a file called "STA130-F21-final-
project-template".
Individuals and groups can book a consultation with a TA about their project plan. Slots are
available most days between November 15–27.
There are three components due: the report
(https://q.utoronto.ca/courses/235890/assignments/735886) (Dec 3), a peer review
(https://q.utoronto.ca/courses/235890/assignments/735888) (Dec 9), and a self-reflection
(https://q.utoronto.ca/courses/235890/assignments/735887) (Dec 9).
Use the project checklist (https://q.utoronto.ca/courses/235890/pages/project-checklist) and the
rubric (https://q.utoronto.ca/courses/235890/assignments/735886) to make sure you're on track.
Key links
Launch video here (https://q.utoronto.ca/courses/235890/pages/project-launch) .
Interview with our collaborators here (https://q.utoronto.ca/courses/235890/pages/interview-
with-prof-adam-hammond-and-prof-simon-stern-on-the-birth-of-the-modern-detective-story) .
Group agreement: [.docx] (https://q.utoronto.ca/courses/235890/files/17140776?wrap=1)
(https://q.utoronto.ca/courses/235890/files/17140776/download?download_frd=1) [.pdf]
(https://q.utoronto.ca/courses/235890/files/17140780?wrap=1)
(https://q.utoronto.ca/courses/235890/files/17140780/download?download_frd=1)
Group registration (https://forms.office.com/r/TmZqeipw9p)
✅Project checklist (https://q.utoronto.ca/courses/235890/pages/project-checklist)
Load project template and data on the JupyterHub (https://jupyter.utoronto.ca/hub/user-
redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2FUofT-sta130%2FSTA130-F21-final-project-
template&urlpath=rstudio%2F&branch=main)
Assessments
2021/12/1 下午3:14 Project overview: STA130H1 F 20219:An Introduction to Statistical Reasoning and Data Science
https://q.utoronto.ca/courses/235890/pages/project-overview 2/5
There will be 4 project associated assessments due:
Proposal (https://q.utoronto.ca/courses/235890/assignments/711998) due on Thursday Oct 21,
2021 at 11:59 a.m. ET (15% of your project grade)
Final Report (https://q.utoronto.ca/courses/235890/assignments/735886) due on Friday Dec 3,
2021 at 11:59 a.m. ET (75% of your project grade)
Peer Review (https://q.utoronto.ca/courses/235890/assignments/735888) due on Thursday Dec
9, 2021 at 11:59 a.m. ET (5% of your project grade)
Self Reflection (https://q.utoronto.ca/courses/235890/assignments/735887) due on Thursday
Dec 9, 2021 at 11:59 a.m. ET (5% of your project grade)
Group work
You have the option of working as an individual or in a group of 2–4 total students (including
you) for the "content" submission (everyone must complete the project proposal, peer evaluation,
and project reflection individually). However, it is entirely reasonable for you to complete the
project as an individual. You will have from November 4 until Tuesday, November 23, 11:59
a.m. to sign up as a group. After this time, we will assume that students who have NOT
registered as a group will be completing the project as individuals.
If you would like to work with a group, you need to find people who you would like to work with.
Here are some ideas of ways to form groups:
Asking your fellow discussion group members if they'd like to work with you as a group for the
final project (either in the weekly synchronous meetings or in the introductions discussion
board).
Using the "Find group members" feature in Piazza.
Registering your group
Once you have found a group to work with, your group must submit one copy of this form
(https://forms.office.com/r/TmZqeipw9p) together. To complete the form, you will need:
A group name,
the full name (as it appears on Quercus), U of T email address (@mail.utoronto.ca — check
carefully for typos, this will be used to match you on Quercus!), and UTORid (NOT student ID,
your UTORID is what you use to log in to Quercus and should be made of letters from your
name and possibly some numbers) for each member, and
A signed copy of this group contract ([.docx]
(https://q.utoronto.ca/courses/235890/files/17140776?wrap=1)
(https://q.utoronto.ca/courses/235890/files/17140776/download?download_frd=1) [.pdf]
(https://q.utoronto.ca/courses/235890/files/17140780?wrap=1)
(https://q.utoronto.ca/courses/235890/files/17140780/download?download_frd=1) ) from each
member saved as a PDF.
2021/12/1 下午3:14 Project overview: STA130H1 F 20219:An Introduction to Statistical Reasoning and Data Science
https://q.utoronto.ca/courses/235890/pages/project-overview 3/5
Sign up for an optional consultation with a TA about
your project proposal/project (Nov 15–27, first come,
first serve)
The purpose of these optional consultations is to help you chat about the questions you're
thinking about exploring in your final project and the methods you're thinking about using. You're
encouraged to attend with your group members (only one person needs to sign up) if you're
working with a group (the person who books the session will need to share the link with the
others). It is also OK to go alone, even if you're working with a group (just make sure to report
back to your group!)
How to sign up
Follow the instructions here: https://utm.library.utoronto.ca/students/canvas/book-
appointment (https://utm.library.utoronto.ca/students/canvas/book-appointment) . For our course,
you are looking for events called Project proposal feedback (TA ), You can book
whatever time suits you, it does not matter who the TA is (i.e. doesn't have to be your discussion
group TA).
These appointments are available on a first-come-first-served basis, so if you can no longer make
the time you booked, please 'un-reserve' it as soon as possible so that someone else can
access it (see instructions at the bottom of the link above).
Final project content
(https://q.utoronto.ca/courses/235890/assignments/7358
86) (due Friday, Dec 3 at 11:59 a.m. ET)
For this project, you will be helping Professors Adam Hammond (English) and Simon Stern
(Law) on their project, "The Birth of the Modern Detective Story". You'll be exploring what
makes for an enjoyable detective story, focussing on stories from the early 1800s to the early
1900s. Our collaborators interests are broad, so any insights you can give them about interesting
findings from this data is valuable (i.e., does not only have to be about what makes for an
enjoyable story).
You should make sure that your final insights are specific and tied to the data; i.e. not general
recommendations like, "stories should hold the reader's attention" which are not tied to these
data. You may consider searching for additional sources of data to combine with this data if you
Load project template and data on the JupyterHub ("STA130-F21-final-project-
template") (https://jupyter.utoronto.ca/hub/user-redirect/git-pull?
repo=https%3A%2F%2Fgithub.com%2FUofT-sta130%2FSTA130-F21-final-project-
template&urlpath=rstudio%2F&branch=main)
2021/12/1 下午3:14 Project overview: STA130H1 F 20219:An Introduction to Statistical Reasoning and Data Science
https://q.utoronto.ca/courses/235890/pages/project-overview 4/5
wish, but you are expected to use the data provided (see data description on the Project
proposal (https://q.utoronto.ca/courses/235890/assignments/711998) page).
The above objective is very broad, so in your project, you will need to formulate specific questions
to help your collaborators. You are not required to use the same questions as you formulated in
your project proposal, but we expect that those questions (and/or the feedback you received on
them) will be useful in helping you think about the elements of interesting and meaningful
questions for your audience (Profs Hammond and Stern).
General comments on this Project
We expect that your analysis will require data wrangling, exploratory data analysis (plots
and summary statistics), and statistical methods (e.g. hypothesis tests, confidence intervals,
classification trees, and/or regression models). Your project should NOT include all of the
statistical methods we've learned.
You do not need to use all of the variables in the dataset and are encouraged to
create new variables from the data and/or link outside datasets that may be more suitable for
answering relevant questions.
You might also choose not to include all observations in your analyses. Think carefully about
what questions your group would like to explore and the story you are telling with your
analysis.
Make sure that the visualizations and methods you choose to use make sense for the
questions you are trying to answer! Some of the statistical methods we covered in this course
are not useful to answer certain research questions, and choosing appropriate methods to
answer each of your questions is an important part of this project. The visualizations you
choose should be meaningful for your audience (Profs Hammond and Stern)
How to create the slide deck?
You must create your slide deck using RMarkdown, and it must knit to pdf. Here is a template
(https://jupyter.utoronto.ca/hub/user-redirect/git-pull?
repo=https%3A%2F%2Fgithub.com%2FUofT-sta130%2FSTA130-F21-final-project-
template&urlpath=rstudio%2F&branch=main) to help you get started (same link as the orange
button above).
When using the template, we suggest you start by saving a personal copy of the template,
so that you keep a copy of the original in your JupyterHub folder for reference.
In your copy, you may want to keep some of the titles the same (e.g. Introduction,
Conclusion, etc), but will want to replace most of the text/images with content related to
your specific work. The examples in the template are there to show you the kinds of
formatting options that are available to you.
If you have formatting questions (i.e. how do I resize an image in my slides), you should:
1. Search on Piazza to see if anyone else has asked the same question
2. Post your question on Piazza
3. Come to TA/instructor office hours to ask your question
Your slide deck must be no more than 18 slides, including the title slide (you may have an
extra slide if references/acknowledgment slides are appropriate for your project)
2021/12/1 下午3:14 Project overview: STA130H1 F 20219:An Introduction to Statistical Reasoning and Data Science
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The goal is not to carry out an exhaustive analysis, nor to apply everything you have
learned in the course. The goal is to demonstrate that:
you have learned how to use R,
you can appropriately apply the methods we have covered in class to address a
question, and that
you can effectively interpret and communicate the results.
Self-check
Make sure you're ready to submit with this Project checklist
(https://q.utoronto.ca/courses/235890/pages/project-checklist) . Remember that the final project
rubric (available at the bottom of this page
(https://q.utoronto.ca/courses/235890/assignments/735886) ) is how we will be evaluating your
content submission.
Peer review
(https://q.utoronto.ca/courses/235890/assignments/7358
88) and reflection activity
(https://q.utoronto.ca/courses/235890/assignments/7358
87) (due Thursday, December 9 at 11:59 a.m. ET)
You will be assigned a peer's project at 6:00 pm ET on Friday, December 3, and you will have
until Thursday, December 9 at 11:59 a.m. ET to complete and submit your peer review and
reflection. You will be able to see a link to it in the right-side panel of the Project content
submission (https://q.utoronto.ca/courses/235890/assignments/735886) page, when it is available.
Important note: Peer review is NOT submitted on the project content submission page, this just
allows you to view your assigned projects. You MUST only submit your peer review through the
Project peer review (https://q.utoronto.ca/courses/235890/assignments/735888) survey. Every year