Getting Started

]

# Week 1: .fancy[Getting Started]

### <svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:white;overflow:visible;position:relative;"><path d="M243.4 2.6l-224 96c-14 6-21.8 21-18.7 35.8S16.8 160 32 160v8c0 13.3 10.7 24 24 24H456c13.3 0 24-10.7 24-24v-8c15.2 0 28.3-10.7 31.3-25.6s-4.8-29.9-18.7-35.8l-224-96c-8.1-3.4-17.2-3.4-25.2 0zM128 224H64V420.3c-.6 .3-1.2 .7-1.8 1.1l-48 32c-11.7 7.8-17 22.4-12.9 35.9S17.9 512 32 512H480c14.1 0 26.5-9.2 30.6-22.7s-1.1-28.1-12.9-35.9l-48-32c-.6-.4-1.2-.7-1.8-1.1V224H384V416H344V224H280V416H232V224H168V416H128V224zm128-96c-17.7 0-32-14.3-32-32s14.3-32 32-32s32 14.3 32 32s-14.3 32-32 32z"/></svg> EMSE 6035: Marketing Analytics for Design Decisions
### <svg aria-hidden="true" role="img" viewBox="0 0 448 512" style="height:1em;width:0.88em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:white;overflow:visible;position:relative;"><path d="M272 304h-96C78.8 304 0 382.8 0 480c0 17.67 14.33 32 32 32h384c17.67 0 32-14.33 32-32C448 382.8 369.2 304 272 304zM48.99 464C56.89 400.9 110.8 352 176 352h96c65.16 0 119.1 48.95 127 112H48.99zM224 256c70.69 0 128-57.31 128-128c0-70.69-57.31-128-128-128S96 57.31 96 128C96 198.7 153.3 256 224 256zM224 48c44.11 0 80 35.89 80 80c0 44.11-35.89 80-80 80S144 172.1 144 128C144 83.89 179.9 48 224 48z"/></svg> John Paul Helveston
### <svg aria-hidden="true" role="img" viewBox="0 0 448 512" style="height:1em;width:0.88em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:white;overflow:visible;position:relative;"><path d="M152 64H296V24C296 10.75 306.7 0 320 0C333.3 0 344 10.75 344 24V64H384C419.3 64 448 92.65 448 128V448C448 483.3 419.3 512 384 512H64C28.65 512 0 483.3 0 448V128C0 92.65 28.65 64 64 64H104V24C104 10.75 114.7 0 128 0C141.3 0 152 10.75 152 24V64zM48 448C48 456.8 55.16 464 64 464H384C392.8 464 400 456.8 400 448V192H48V448z"/></svg> August 30, 2023

]

---

# Week 1: .fancy[Getting Started]

### 1. Course orientation
### 2. Intro to conjoint analysis
### 3. Introductions

### BREAK: Teaming

### 4. Getting started with R & RStudio

---

# Week 1: .fancy[Getting Started]

### 1. .orange[Course orientation]
### 2. Intro to conjoint analysis
### 3. Introductions

### BREAK: Teaming

### 4. Getting started with R & RStudio

---

# Meet your instructor!

]]

### John Helveston, Ph.D.

- 2018 - Present Assistant Professor, Engineering Management & Systems Engineering
- 2016-2018 Postdoc at [Institute for Sustainable Energy](https://www.bu.edu/ise/), Boston University
- 2016 PhD in Engineering & Public Policy at Carnegie Mellon University
- 2015 MS in Engineering & Public Policy at Carnegie Mellon University
- 2010 BS in Engineering Science & Mechanics at Virginia Tech
- Website: [www.jhelvy.com](http://www.jhelvy.com/)

]]

---

# <svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M78.6 5C69.1-2.4 55.6-1.5 47 7L7 47c-8.5 8.5-9.4 22-2.1 31.6l80 104c4.5 5.9 11.6 9.4 19 9.4h54.1l109 109c-14.7 29-10 65.4 14.3 89.6l112 112c12.5 12.5 32.8 12.5 45.3 0l64-64c12.5-12.5 12.5-32.8 0-45.3l-112-112c-24.2-24.2-60.6-29-89.6-14.3l-109-109V104c0-7.5-3.5-14.5-9.4-19L78.6 5zM19.9 396.1C7.2 408.8 0 426.1 0 444.1C0 481.6 30.4 512 67.9 512c18 0 35.3-7.2 48-19.9L233.7 374.3c-7.8-20.9-9-43.6-3.6-65.1l-61.7-61.7L19.9 396.1zM512 144c0-10.5-1.1-20.7-3.2-30.5c-2.4-11.2-16.1-14.1-24.2-6l-63.9 63.9c-3 3-7.1 4.7-11.3 4.7H352c-8.8 0-16-7.2-16-16V102.6c0-4.2 1.7-8.3 4.7-11.3l63.9-63.9c8.1-8.1 5.2-21.8-6-24.2C388.7 1.1 378.5 0 368 0C288.5 0 224 64.5 224 144l0 .8 85.3 85.3c36-9.1 75.8 .5 104 28.7L429 274.5c49-23 83-72.8 83-130.5zM104 432c0 13.3-10.7 24-24 24s-24-10.7-24-24s10.7-24 24-24s24 10.7 24 24z"/></svg> Tools

<br>

## <svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M352 256c0 22.2-1.2 43.6-3.3 64H163.3c-2.2-20.4-3.3-41.8-3.3-64s1.2-43.6 3.3-64H348.7c2.2 20.4 3.3 41.8 3.3 64zm28.8-64H503.9c5.3 20.5 8.1 41.9 8.1 64s-2.8 43.5-8.1 64H380.8c2.1-20.6 3.2-42 3.2-64s-1.1-43.4-3.2-64zm112.6-32H376.7c-10-63.9-29.8-117.4-55.3-151.6c78.3 20.7 142 77.5 171.9 151.6zm-149.1 0H167.7c6.1-36.4 15.5-68.6 27-94.7c10.5-23.6 22.2-40.7 33.5-51.5C239.4 3.2 248.7 0 256 0s16.6 3.2 27.8 13.8c11.3 10.8 23 27.9 33.5 51.5c11.6 26 21 58.2 27 94.7zm-209 0H18.6C48.6 85.9 112.2 29.1 190.6 8.4C165.1 42.6 145.3 96.1 135.3 160zM8.1 192H131.2c-2.1 20.6-3.2 42-3.2 64s1.1 43.4 3.2 64H8.1C2.8 299.5 0 278.1 0 256s2.8-43.5 8.1-64zM194.7 446.6c-11.6-26-20.9-58.2-27-94.6H344.3c-6.1 36.4-15.5 68.6-27 94.6c-10.5 23.6-22.2 40.7-33.5 51.5C272.6 508.8 263.3 512 256 512s-16.6-3.2-27.8-13.8c-11.3-10.8-23-27.9-33.5-51.5zM135.3 352c10 63.9 29.8 117.4 55.3 151.6C112.2 482.9 48.6 426.1 18.6 352H135.3zm358.1 0c-30 74.1-93.6 130.9-171.9 151.6c25.5-34.2 45.2-87.7 55.3-151.6H493.4z"/></svg> Course website: https://madd.seas.gwu.edu/2023-Fall/

## <svg aria-hidden="true" role="img" viewBox="0 0 448 512" style="height:1em;width:0.88em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M94.12 315.1c0 25.9-21.16 47.06-47.06 47.06S0 341 0 315.1c0-25.9 21.16-47.06 47.06-47.06h47.06v47.06zm23.72 0c0-25.9 21.16-47.06 47.06-47.06s47.06 21.16 47.06 47.06v117.84c0 25.9-21.16 47.06-47.06 47.06s-47.06-21.16-47.06-47.06V315.1zm47.06-188.98c-25.9 0-47.06-21.16-47.06-47.06S139 32 164.9 32s47.06 21.16 47.06 47.06v47.06H164.9zm0 23.72c25.9 0 47.06 21.16 47.06 47.06s-21.16 47.06-47.06 47.06H47.06C21.16 243.96 0 222.8 0 196.9s21.16-47.06 47.06-47.06H164.9zm188.98 47.06c0-25.9 21.16-47.06 47.06-47.06 25.9 0 47.06 21.16 47.06 47.06s-21.16 47.06-47.06 47.06h-47.06V196.9zm-23.72 0c0 25.9-21.16 47.06-47.06 47.06-25.9 0-47.06-21.16-47.06-47.06V79.06c0-25.9 21.16-47.06 47.06-47.06 25.9 0 47.06 21.16 47.06 47.06V196.9zM283.1 385.88c25.9 0 47.06 21.16 47.06 47.06 0 25.9-21.16 47.06-47.06 47.06-25.9 0-47.06-21.16-47.06-47.06v-47.06h47.06zm0-23.72c-25.9 0-47.06-21.16-47.06-47.06 0-25.9 21.16-47.06 47.06-47.06h117.84c25.9 0 47.06 21.16 47.06 47.06 0 25.9-21.16 47.06-47.06 47.06H283.1z"/></svg> Course slack: https://emse-madd-f23.slack.com

## <svg aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:1em;width:1.13em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg> & RStudio: [Course Software Page](https://madd.seas.gwu.edu/2023-Fall/software.html)

---

# Why <svg aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:1em;width:1.13em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>?

---

# Learning Objectives

### After this class, you will know how to...

- ### ...work with data in <svg aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:1em;width:1.13em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg>
- ### ...design effective surveys to get rich data
- ### ...analyze consumer choice data to model consumer preferences
- ### ...design effective charts to communicate insights

---

# Course prerequisites

### This course requires prior exposure to:

- ### Probability theory
- ### Multivariable calculus
- ### Linear algebra
- ### Regression
]

### **Not sure?**

### Take [this self assessment](https://madd.seas.gwu.edu/2023-Fall/self-assessment.html)

]

---

# Reflections (30% of grade)

### Do some readings, recorded lectures, practice problems

### Write a short reflection

---

# **Quizzes** (10% of grade)

> **Why quiz at all?** The "retrieval effect" - basically, you have to _practice_ remembering things, otherwise your brain won't remember them (see the book ["Make It Stick: The Science of Successful Learning"](https://www.hup.harvard.edu/catalog.php?isbn=9780674729018))

---

# Exam (10% of grade)

### Take home exam, 2nd to last week of class

### We'll go over exam solutions on last day of class

---

# [Semester Project](https://madd.seas.gwu.edu/2023-Fall/project/0-overview.html) (45% of grade)

### Teams of 3-4 students

### Goals:

- Assess market viability of a new technology or design
- Recommend best design choices for target market or application

]

### Key deliverables:

Item            | Weight | Due
----------------|----------------------------|--------------------
Project Proposal      | 5 %    | Sep. 24
Survey Plan           | 5 %    | Oct. 03
Pilot Survey          | 5 %    | Oct. 17
Pilot Analysis        | 5 %    | Nov. 05
Final Survey          | 5 %    | Nov. 19
Final Analysis Report | 15 %   | Dec. 10
Final Presentation    | 5 %    | Dec. 12

]

---

background-color: #FFF

# .center[Grades]

---

# .center[Grades]

Item                  | Weight | Notes
----------------------|--------|-------------------------------------
Participation / Attendance | 5%     | (Yes, I take attendance)
Reflections           | 30 %   | Weekly assignment (10 x 3%, lowest dropped)
Quizzes               | 10 %    | 5 quizzes, lowest dropped
Final Exam            | 10 %   | Take home exam
Project Proposal      | 5 %    | Teams of 3-4 students
Survey Plan           | 5 %    |
Pilot Survey          | 5 %    |
Pilot Analysis        | 5 %    |
Final Survey          | 5 %    |
Final Analysis Report | 15 %   |
Final Presentation    | 5 %    |

---

# Course policies

- ## BE NICE
- ## BE HONEST
- ## DON'T CHEAT

]

## .center[Copying is good, stealing is bad]

> "Plagiarism is trying to pass someone else's work off as your own. Copying is about reverse-engineering."
>
> .right[-- Austin Kleon, from [Steal Like An Artist](https://austinkleon.com/steal/)&ensp;]

]

---

## Use of chatGPT and other AI tools

- Large language models (LLMs) are pretty good...but sometimes suck.

--
 
- Use of AI tools is generally permitted, but **be transparent**.

- All assignments must include a **Use of AI on this assignment** section where you:

- Describe any AI tool and how it was used along with prompt(s) used.
    - Include a link to the chat transcript.

## **Use AI as an assistant, not a solutions manual**

> Curious how LLMs actually work? Check out [this article](https://www.understandingai.org/p/large-language-models-explained-with), which provides a simplified description of how they work (which itself is still quite complicated).

---

# Late submissions

## - **5** late days - use them anytime, no questions asked
## - No more than **2** late days on any one assignment
## - Contact me for special cases

---

# How to succeed in this class

## <svg aria-hidden="true" role="img" viewBox="0 0 640 512" style="height:1em;width:1.25em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M144 160c-44.2 0-80-35.8-80-80S99.8 0 144 0s80 35.8 80 80s-35.8 80-80 80zm368 0c-44.2 0-80-35.8-80-80s35.8-80 80-80s80 35.8 80 80s-35.8 80-80 80zM0 298.7C0 239.8 47.8 192 106.7 192h42.7c15.9 0 31 3.5 44.6 9.7c-1.3 7.2-1.9 14.7-1.9 22.3c0 38.2 16.8 72.5 43.3 96c-.2 0-.4 0-.7 0H21.3C9.6 320 0 310.4 0 298.7zM405.3 320c-.2 0-.4 0-.7 0c26.6-23.5 43.3-57.8 43.3-96c0-7.6-.7-15-1.9-22.3c13.6-6.3 28.7-9.7 44.6-9.7h42.7C592.2 192 640 239.8 640 298.7c0 11.8-9.6 21.3-21.3 21.3H405.3zM416 224c0 53-43 96-96 96s-96-43-96-96s43-96 96-96s96 43 96 96zM128 485.3C128 411.7 187.7 352 261.3 352H378.7C452.3 352 512 411.7 512 485.3c0 14.7-11.9 26.7-26.7 26.7H154.7c-14.7 0-26.7-11.9-26.7-26.7z"/></svg> Participate during class!

## <svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M469.3 19.3l23.4 23.4c25 25 25 65.5 0 90.5l-56.4 56.4L322.3 75.7l56.4-56.4c25-25 65.5-25 90.5 0zM44.9 353.2L299.7 98.3 413.7 212.3 158.8 467.1c-6.7 6.7-15.1 11.6-24.2 14.2l-104 29.7c-8.4 2.4-17.4 .1-23.6-6.1s-8.5-15.2-6.1-23.6l29.7-104c2.6-9.2 7.5-17.5 14.2-24.2zM249.4 103.4L103.4 249.4 16 161.9c-18.7-18.7-18.7-49.1 0-67.9L94.1 16c18.7-18.7 49.1-18.7 67.9 0l19.8 19.8c-.3 .3-.7 .6-1 .9l-64 64c-6.2 6.2-6.2 16.4 0 22.6s16.4 6.2 22.6 0l64-64c.3-.3 .6-.7 .9-1l45.1 45.1zM408.6 262.6l45.1 45.1c-.3 .3-.7 .6-1 .9l-64 64c-6.2 6.2-6.2 16.4 0 22.6s16.4 6.2 22.6 0l64-64c.3-.3 .6-.7 .9-1L496 350.1c18.7 18.7 18.7 49.1 0 67.9L417.9 496c-18.7 18.7-49.1 18.7-67.9 0l-87.4-87.4L408.6 262.6z"/></svg> Start assignments early and **read carefully**!

## <svg aria-hidden="true" role="img" viewBox="0 0 640 512" style="height:1em;width:1.25em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M176 48c0 26.5-21.5 48-48 48s-48-21.5-48-48s21.5-48 48-48s48 21.5 48 48zM144 241.7v65.1l51 51c7.1 7.1 11.8 16.2 13.4 26.1l15.2 90.9c2.9 17.4-8.9 33.9-26.3 36.8s-33.9-8.9-36.8-26.3l-14.3-85.9L66.8 320C54.8 308 48 291.7 48 274.7V186.6c0-32.4 26.2-58.6 58.6-58.6c24.1 0 46.5 12 59.9 32l47.4 71.1 10.1 5V160c0-17.7 14.3-32 32-32H384c17.7 0 32 14.3 32 32v76.2l10.1-5L473.5 160c13.3-20 35.8-32 59.9-32c32.4 0 58.6 26.2 58.6 58.6v88.1c0 17-6.7 33.3-18.7 45.3l-79.4 79.4-14.3 85.9c-2.9 17.4-19.4 29.2-36.8 26.3s-29.2-19.4-26.3-36.8l15.2-90.9c1.6-9.9 6.3-19 13.4-26.1l51-51V241.7l-19 28.5c-4.6 7-11 12.6-18.5 16.3l-59.6 29.8c-2.4 1.3-4.9 2.2-7.6 2.8c-2.6 .6-5.3 .9-7.9 .8H256.7c-2.5 .1-5-.2-7.5-.7c-2.9-.6-5.6-1.6-8.1-3l-59.5-29.8c-7.5-3.7-13.8-9.4-18.5-16.3l-19-28.5zM2.3 468.1L50.1 348.6l49.2 49.2-37.6 94c-6.6 16.4-25.2 24.4-41.6 17.8S-4.3 484.5 2.3 468.1zM512 96c-26.5 0-48-21.5-48-48s21.5-48 48-48s48 21.5 48 48s-21.5 48-48 48zm77.9 252.6l47.8 119.5c6.6 16.4-1.4 35-17.8 41.6s-35-1.4-41.6-17.8l-37.6-94 49.2-49.2z"/></svg> Ask for help!

---

# Getting Help

- Mondays from 8:00-4:30pm
- Tuesdays from 8:00-4:30pm
- Fridays from 8:00-4:00pm

---

# Week 1: .fancy[Getting Started]

### 1. Course orientation
### 2. .orange[Intro to conjoint analysis]
### 3. Introductions

### BREAK: Teaming

### 4. Getting started with R & RStudio

---

]

# Engineers often design things nobody wants!

]

---

## We want to answers to questions like...

<br>

### - Higher prices decrease demand, but by how much?

### - How much more is a consumer willing to pay for increased performance in X?

### - How will my product compete against competitors in the market?

## **Answers depend on knowing what people want**

---

## Directly asking people what they want isn't always helpful

### (People want everything)

---

## Which feature do you care more about?

## .center[Battery Life?]

]

## .center[Brand?]

]

## .center[Signal quality?]

]

---

## **Conjoint approach**:<br>Use consumer choice data to model preferences

---

### .center[Use random utility framework to predict probability of choosing phone _j_]

<br>

### 1. `$u_j = \beta_1\mathrm{price}_j + \beta_2\mathrm{brand}_j + \beta_3\mathrm{battery}_j + \beta_4\mathrm{signal}_j + \varepsilon_j$`

### 2. Assume `$\varepsilon_j \sim$` iid extreme value

### 3. Probability of choosing phone _j_: `$P_j = \frac{e^{\beta'x_j}}{\sum_k^J e^{\beta'x_k}}$`

### 4. Estimate `$\beta_1$`, `$\beta_2$`, `$\beta_3$`, `$\beta_4$` by minimizing `$-L = - \sum_n^N \sum_j^J y_{nj} \ln P_{nj}$`

---

## **Willingness to Pay**

<br>

## `$u_j = \beta'x_j + \alpha p_j + \varepsilon_j$`

## `$\omega = \frac{\beta}{-\alpha}$`

]]

## **Make predictions**

### `$P_j = \frac{e^{\hat{\beta}'x_j}}{\sum_k^J e^{\hat{\beta}'x_k}}$`

]

---

# Example: _Pocket Charge_

## A Flexible, Portable Solar Charger

---

---

### Example survey choice question

---

---

# Your project starts now!

# [View project Ideas](https://docs.google.com/presentation/d/1bNnsKWkU8FwGHIL_jK72ilXsvhZhr98Q/edit?usp=sharing)

---

# Week 1: .fancy[Getting Started]

### 1. Course orientation
### 2. Intro to conjoint analysis
### 3. .orange[Introductions]

### BREAK: Teaming

### 4. Getting started with R & RStudio

---

# Introduce yourself

## - Preferred name
## - Degree program
## - Prior experience
## - What do you hope to gain from this class?
## - Project interests?

---

<br>

# .center[.fancy[Break]]

1. If you haven't already, install everything on the [software page](https://madd.seas.gwu.edu/2023-Fall/software.html)

2. Stand up, meet each other, (maybe form teams?...use [this sheet](https://docs.google.com/spreadsheets/d/1Y-ApfpujwbywjL05KCmUo-AzZqRheqq7_M_vLuEnjt0/edit?usp=sharing))

---

# Week 1: .fancy[Getting Started]

### 1. Course orientation
### 2. Intro to conjoint analysis
### 3. Introductions

### BREAK: Teaming

### 4. .orange[Getting started with R & RStudio]

---

# RStudio Orientation

]

- Know the boxes
- Customize the layout
- Customize the look
- [Extra themes](https://github.com/gadenbuie/rsthemes)

]

---

# Open `intro-to-R.R` file and follow along

---

# View prior code in history pane

# Use "up" arrow see previous code

---

# Staying organized

## 1) Save your code in .R files

> ### &zwj;File > New File > R Script

## 2) Keep work in R Project files

> ### File > New Project...

---

## Your turn

### A. Practice getting organized

1. Open RStudio and create a new R project called `week1`.
2. Create a new R script and save it as `practice.R`.
3. Open the `practice.R` file and write your answers to these questions in it.

]]

### B. Creating & working with objects

1). Create objects to store the values in this table:

| City              | Area (sq. mi.) | Population (thousands) |
|-------------------|----------------|------------------------|
| San Francisco, CA | 47             | 884                    |
| Chicago, IL       | 228            | 2,716                  |
| Washington, DC    | 61             | 694                    |

2) Using the objects you created, answer the following questions:

- Which city has the highest density?
  - How many _more_ people would need to live in DC for it to have the same population density as San Francisco?

]]

---

# >15,000 [packages](https://cran.r-project.org/web/packages/available_packages_by_name.html) on the [CRAN](https://cran.r-project.org/)

---

# Installing packages

### `install.packages("packagename")`
### (The package name **must** be in quotes)

```r
install.packages("packagename") # This works
install.packages(packagename)   # This doesn't work
```

### **You only need to install a package once!**

---

# Loading packages

### `library(packagename)`: Loads all the functions in a package
### (The package name _doesn't_ need to be in quotes)

```r
library("packagename") # This works
library(packagename)   # This also works
```

### **You need to _load_ the package every time you use it!**

---

background-color: #fff
class: center

# Installing vs. Loading

---

## Example: **wikifacts**

Install the [Wikifacts](https://github.com/keithmcnulty/wikifacts) package, by Keith McNulty:

```r
install.packages("wikifacts")
```

Load the package:

```r
library(wikifacts) # Load the library
```

Use one of the package functions

```r
wiki_randomfact()
```

```
#> [1] "Did you know that when Josette Simon appeared as Rosaline in Love's Labour's Lost, she was the first black woman in a lead role at the Royal Shakespeare Company? (Courtesy of Wikipedia)"
```

---

## Example: **wikifacts**

Now, restart your RStudio session:
> Session -> Restart R

Try using the package function again:

```r
wiki_randomfact()
```

```
#> Error in wiki_randomfact(): could not find function "wiki_randomfact"
```

---

# Using only _some_ package functions

### You don't always have to load the whole library.

### Functions can be accessed with this pattern:
`packagename::functionname()`

```r
wikifacts::wiki_randomfact()
```

```
#> [1] "Did you know that on March 21 in 2006 – A man using a hammer smashed the statue of Phra Phrom (pictured) in the Erawan Shrine in Bangkok, Thailand, and was subsequently beaten to death by bystanders. (Courtesy of Wikipedia)"
```

---

## If you haven't yet, install [these packages](https://raw.githubusercontent.com/emse-madd-gwu/2023-Fall/main/content/packages.R)

---

# Back `intro-to-R.R` for the rest of class!