R and RStudio

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## Before lecture begins, go to the Stat 100 Slack Workspace and answer the question in the #inspiration channel.

### The Slack Workspace can be accessed through our Canvas page.

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## .base-blue[Computing in Stat 100]

### .purple[Kelly McConville]

#### .purple[ Stat 100 | Week 2 | Fall 2022]

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## Announcements

* Section and wrap-up sessions start this week!
* You have now been assigned to a section.
    + If you'd like to move sections, fill out [this form](https://forms.gle/q7x3Vf2xp2h396fK7) by the end of today.
    + We likely won't be able to honor all requests but will do what we can.
* First lecture quiz will be released on Gradescope at 11:45am today and is due by Friday morning at 11:45am.
  + Open notes and open book but not open people.
  + Not timed.

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## Goals for Today

* Stat 100 structure and assessments
* Getting up and running in `RStudio`
* Working with `RMarkdown` documents

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## Overarching Goal:

### Learn how to .orange[extract knowledge] from data.

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###  Course Learning Objectives

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* Learn how to **analyze** data.

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* Acquire good data **habits**.

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* Develop **statistical thinking** and **problem-solving** skills.

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## Data Analysis Workflow

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## Data Analysis Workflow

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## Data Analysis Workflow

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## Data Analysis Workflow

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###  Data Analysis Workflow

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* Not a strict set of guidelines.

* General structure for **extracting knowledge from data**.

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* Consider **iteration** throughout.

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* Consider **reproducibility** throughout.

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* Consider **ethics** throughout.

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## Stat 100 Tech & Materials

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## Stat 100 Weekly Flow

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## Forms of Assessment

* **Weekly lecture quizzes:**
    + Address important concepts covered.
    + Find out what is still confusing.
    + Can drop one quiz grade.

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* **Weekly problem sets:**
    + Practice concepts.
    + Time during section will be devoted to starting the next p-set.
    + Can drop one problem set grade.

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* **Exams:** 
    + Format: Takehome Exam followed by Oral Exam
    + Will have both a Mid-term and Final.

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* **Group project:**
    + Practice applying data analysis process to a research question.

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* **Participation/Engagement:**
    + In lecture and section.
    + By Oct 14th, must:
        + Attend at least one office hour.
        + Post at least two messages on Slack.

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+ Asking a question about course content

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+ Answering someone else's question

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+ Posting a useful resource and why you found it helpful

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+ Creating an example that illustrates a recent concept

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If you have never used Slack before, don't worry.  We are here to help!

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## This Week's Assessments

* **Week 2 Lecture Quiz** will be posted on Gradescope right after lecture today.
    + Due by Friday at 11:45am
* **P-Set 1** is posted to the RStudio Server.
    + We will access it later in class.
    + You will need a postcard to start visualizing your data!
    + Due on Tuesday, September 13th at 5pm on Gradescope.

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### Problem 1 of Problem Set 1: Create your own Dear Data postcard!

**Step 1**

* Collect data on some aspect of your life.
    
**Step 2**    
    
* Find a story in your data and determine your postcard recipient.

* Figure out how you want to visualize the story.

**Step 3+**

* Visualize your data on a blank postcard.

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## Engagement

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* Being **actively present** is key.
{{content}}

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* During lecture and section, remove distractions.
    + When we are on our computers, close email, social media, news, etc.
    + If you will be using a computer/tablet for taking notes, please sit in the technology zone **starting next lecture** so as not to distract classmates.
    + Hide your phone.
{{content}}

* What you get out of Stat 100 will depend on what you put into it.
{{content}}

* I have high expectations but know that all of you (regardless of your stats or computing background) have the ability to meet them.
{{content}}

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## Identity and the Classroom

* Acknowledge that my perspectives and experiences have shaped how I teach this course

* Some of my identities place me in dominant groups while others in marginalized groups

* Strive to bring examples and scholarly contributions that value knowledge from folks with a wide variety of identities

* Strive to be a open listener and recognize your thoughts as a generous offer and a vote of confidence in my ability to hear and be transformed by you

* Ask that you reflect on your own identities, privileges, and power and how they impact your engagement with Stat 100

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## Code of Conduct

I expect all members of STAT 100 to make participation a harassment-free experience for everyone, regardless of age, body size, visible or invisible disability, ethnicity, sex characteristics, gender identity and expression, level of experience, education, socio-economic status, nationality, personal appearance, race, religion, or sexual identity and orientation.

I expect everyone to act and interact in ways that contribute to an open, welcoming diverse, inclusive, and healthy community of learners.  You can contribute to a positive learning environment by demonstrating empathy and kindness, being respectful of differing viewpoints and experiences, and giving and gracefully accepting constructive feedback.

This Code of Conduct is adapted from the [Contributor Covenant](https://www.contributor-covenant.org/version/2/0/code_of_conduct.html), version 2.0.

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## Ways to Get Support

* **Attend, attend, attend** when you don't feel ill

* **Participate** in the Stat 100 Slack Workspace

* **Come** to Office Hours

* **Create** study groups with your classmates
    + Natural groups: project group members, folks in your same section

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## Computation in Stat 100

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## Computation

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## Computation

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## Computation

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### Getting Help with `R`

#### .center[Novices asking the internet for `R` help = 😰]

* **Get help from the Stat 100 teaching staff or classmates!**
    + Will start p-sets in section each week.
    + Use the Slack `#q-and-a` channel.

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* Get help **early** before 😡 sets in!
    + Be prepared for missing commas and quotes, capitalization issues, etc...

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* Later in the semester, will learn tricks for effectively getting `R` help online.

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## Language: `R`-This, `R`-That, `R`-...

Three `R` Things:

`R` is the name of the programming language.

`RStudio` is the pretty interface.

`RMarkdown` is the type of file where we will record all of our work (code, output, narrative).

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## Let's Get Started with `R`!

## First step: Navigate to the class Canvas site.

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## Accessing the RStudio Server

* First time may take a while.

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## Main Components of RStudio Lay-Out

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### Main Components of RStudio Lay-Out

**Console**

* Sideways carrot called **prompt**.

* Where you run code.

* Let's try it:

```r
6 * 2/ 3
```

```
## [1] 4
```

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**Environment**

* Lists items stored in your session.

* Will add some items soon!

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**Files et. al.**

* **Files**: Accesses files in your own directory and the shared directory `shared_data`.

* **Plots**: Contains graphs we create.

* **Packages**: Installs and loads packages.

* **Help**: Displays help files.

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##Accessing Course Materials

* All `R` related course materials will be stored in the `shared_data` folder in the **Files** tab.

* You can access shared files but **you must move the files to your home directory** before you edit and save them.

* Let's practice that now with `introRMarkdown.Rmd` which can be found in `shared_data/stat100/handouts`.

* Steps:
    + Step 1: Click on the `shared_data`, then `stat100`, then `handouts`.
    + Step 2: Click on "introRMarkdown".  It should open in the upper lefthand window.
    + Step 5: Go to the top left of the window and click on File > Save as...
    + Step 6: Click on "Home".
    + Step 7: (Only do this once) Click on **New Folder** and call it "handouts". Hit "Ok".
    + Step 8: Then hit Save.  Now the file is saved in your directory and you are ready to work on it.

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## Questions so far?

## Let's go through the Intro to `RMarkdown` Handout.

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## Practice: How do we access P-Set 1?

### .orange[It is okay if all things R haven't sunk in yet.  It will take the first few weeks for that to happen.]

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## Reminders