Welcome to STA 210!

# Welcome to STA 210!
## Regression Analysis
### Prof. Maria Tackett

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# Welcome!

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## Meet the teaching team: Instructor

### Prof. Maria Tackett

.pull-left[
<img src="img/01/capital-one-logo.jpg" width="75%" style="display: block; margin: auto;" />

]

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## Meet the teaching team: TAs

- Sophie Dalldorf

- Emily Gentles

- Leslie Li

- Jose Pliego San Martin

- Shari Tian

- Aaditya Warrier

- Grace Zhao

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## Check in on Ed Discussion!

- Go to the class Ed Discussion: [edstem.org/us/courses/8350/discussion/565405](https://edstem.org/us/courses/8350/discussion/565405)

- Answer the poll question: **How are you doing?**

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# Regression analysis

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## What is regression analysis?

"In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships among variables. It includes many techniques for modeling and analyzing several variables, when <font class="vocab">**the focus is on the relationship between a dependent variable and one or more independent variables (or 'predictors')**</font>. More specifically, regression analysis helps one understand how the typical value of the dependent variable (or 'criterion variable') changes when any one of the independent variables is varied, while the other independent variables are held fixed."

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# The Course

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## Course FAQ

A - Introductory statistics or probability course 
<br>

A - Yes. We will use the computing language R. 
<br>

.midi[A - Yes and No. The course is primarily focused on application; however, we will discuss some of the mathematics of simple linear regression. There is a new 1-credit course [STA 211: Mathematics of Regression](https://stat.duke.edu/courses/mathematics-regression) to take simultaneously or after this course to dive into more of the mathematics.]

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## Course learning objectives

- Analyze real-world data to answer questions about multivariable relationships.

- Fit and evaluate linear and logistic regression models.

- Assess whether a proposed model is appropriate and describe its limitations.

- Use R Markdown to write reproducible reports and GitHub for version control and collaboration.

- Communicate results from statistical analyses to a general audience.

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## Examples of regression in practice

[New Yorkers Will Pay $56 A Month To Trim A Minute Off Their Commute](https://fivethirtyeight.com/features/new-yorkers-will-pay-56-a-month-to-trim-a-minute-off-their-commute/)

[How FiveThirtyEight’s 2020 Presidential Forecast Works — And What’s Different Because Of COVID-19](https://fivethirtyeight.com/features/how-fivethirtyeights-2020-presidential-forecast-works-and-whats-different-because-of-covid-19/)

[Effect of Forensic Evidence on Criminal Justice Case Processing](https://onlinelibrary.wiley.com/doi/10.1111/1556-4029.12020)

[Why it's so freaking hard to make a good COVID-19 model](https://fivethirtyeight.com/features/why-its-so-freaking-hard-to-make-a-good-covid-19-model/)

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# The Course

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## Course Toolkit

- .vocab[Course website:]
[sta210-fa21.netlify.app](https://sta210-fa21.netlify.app/)
  - Central hub for the course!
  - Quick tour of the website

- .vocab[Sakai:] [sakai.duke.edu](https://sakai.duke.edu)
  - .midi[Gradebook]
  
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## Course Toolkit
  
- .vocab[Ed Discussion: [edstem.org/us/courses/8350/discussion](https://edstem.org/us/courses/8350/discussion/)]
  - Class Q&A and discussion forum

- .vocab[GitHub:] [github.com/sta210-fa21](https://github.com/sta210-fa21)
  - Distribute & work on assignments -- more on this later!
  
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## Activities: Prepare, Practice, Perform

- .vocab[Prepare:] introduce new content and prepare for lectures
  - Videos & readings before lecture
  - Low-stakes prep quizzes on basic definitions & concepts from videos
  - See *Prepare* column on course schedule

- .vocab[Practice:] practice applying statistical concepts and computing
  - Application Exercises (AE) during lecture
  - Graded for completion

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## Activities: Prepare, Practice, Perform

- .vocab[Perform:] Put together what you've learned to analyze real-world data
  -  Weekly team or individual lab assignments
  -  Periodic individual homework assignments
  -  Two take-home exams
  -  Final team project presented during the final exam period.

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## Where to find help

- Attend .vocab[Office hours] to meet with a member of the teaching team.
  - Full office hours begin August 30

- Use **Ed Discussion** for general questions about course content and/or assignments, since other students may benefit from the response.

- Use email for questions regarding personal matters and/or grades.

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## Academic Resource Center

The [Academic Resource Center (ARC)](https://arc.duke.edu/) offers free services to all students during their undergraduate careers at Duke.

Services include 
  - Learning Consultations
  - Peer Tutoring and Study Groups
  - ADHD/LD Coaching, Outreach Workshops
  - and more.

Contact the ARC at [ARC@duke.edu](mailto:arc@duke.edu) or call 919-684-5917 to schedule an appointment.

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## CAPS

[Duke Counseling & Psychological Services (CAPS)](https://studentaffairs.duke.edu/caps) helps Duke Students enhance strengths and develop abilities to successfully live, grow and learn in their personal and academic lives.

Services include 
- brief individual and group counseling
- couples counseling
- outreach to student groups
- and more...

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## Course community & Learning environment

- Uphold the Duke Community Standard: 
> - I will not lie, cheat, or steal in my academic endeavors;
>- I will conduct myself honorably in all my endeavors; and
> - I will act if the Standard is compromised.

- Respect, honor, and celebrate our diverse community

- Learning environment that is welcoming and accessible to everyone

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## Attending lectures and labs

- You are expected to attend and participate lectures and labs

- Please wear a mask to help protect your peers and others around you 😷

- **Please do not come to class if you have symptoms related to COVID-19, have had a known exposure to COVID-19, or have tested positive for COVID-19.**
  - You will still have access to AEs and labs to complete remotely 
  - Online office hours and Ed Discussion are available to ask questions
  - Email Professor Tackett if further arrangements needed
  
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# Questions?

**Raise your hand or post on Ed Discussion**

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# Your turn!

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## Create a GitHub account

.question[
<midi>Go to https://github.com/, and create an account, if needed. Then, go to <a href = "https://bit.ly/sta210-fa21-github">bit.ly/sta210-fa21-github</a> and enter your Duke email address (NETID@duke.edu) and GitHub username.</midi>
]

<small>
Some tips from [Happy Git with R](http://happygitwithr.com/github-acct.html#username-advice).
</small>
- .small[Incorporate your actual name!]
- .small[Use your username from other contexts if you can, e.g., Twitter or Slack.]
- .small[Pick a username you will be comfortable revealing to your future boss.]
- .small[Be as unique as possible in as few characters as possible. Shorter is better than longer.]
- .small[Make it timeless.]
- .small[Avoid words with special meaning in programming (e.g. `NA`).]

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# Let's look at some data!

- Let's take a look at the [Movies budgets vs. revenues](https://sta210-fa21.netlify.app/appex/ae-01-movies.html) analysis.

- You may discuss with your neighbor. (Don't forget to introduce yourself first!)

- Type your answers under the **August 23 - Movies** thread on Ed Discussion

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## For Wednesday

- We'll start talking about the computing toolkit

- Watch videos for [Prepare: Week 01](https://sta210-fa21.netlify.app/prepare/week-01.html)

- Reserve an .vocab[STA210] RStudio container. 
  - Go to https://vm-manage.oit.duke.edu/containers
  - Click **Reserve Container** for the STA210 container
  
- Submit your [GitHub username](https://bit.ly/sta210-fa21-github)

- Bring laptop/tablet/Chromebook to class

- Complete the [Get to Know You survey](https://duke.qualtrics.com/jfe/form/SV_eyUiuqZKsJaqHWK) (by Wed, Sep 01)