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Welcome to STA 199!

Prof. Alexander Fisher

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Meet the teaching team: Instructor

Prof. Alexander Fisher

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Meet the teaching team: TAs

  • Christine Shen

  • Zoey Liu

  • Michael Sarkis

  • Blossom Mojekwu

  • Sara Mehta

  • Mariana Izon

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Data Science

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What is data science?

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What is data science?

  • Data science is using data in a principled way to gain understanding, insight, and knowledge.

  • We're going to learn to do this in a tidy way -- more on that later!

  • This is a course on introduction to data science, with an emphasis on statistical thinking.

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Course FAQ

Q - What data science background does this course assume? A - None.


Q - Is this an intro stat course? A - While statistics data science, they are very closely related and have tremendous of overlap. Hence, this course is a great way to get started with statistics. However this course is not your typical high school statistics course.


Q - Will we be doing computing? A - Yes. We will use the computing language R.

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Course learning objectives

  • Learn to explore, visualize, and analyze data in a reproducible and shareable manner

  • Gain experience in data wrangling, exploratory data analysis, predictive modeling, and data visualization

  • Work on problems and case studies inspired by and based on real-world questions and data

  • Learn to effectively communicate results through written assignments and final project presentation

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Some of what you will learn

  • Fundamentals of R

  • Data visualization and wrangling with ggplot2 and dplyr from the tidyverse

  • Web scraping

  • Web based applications with RShiny

  • Spatial data visualization

  • Data types and functions

  • Version control with GitHub

  • Reproducible reports with R Markdown

  • Regression and classification

  • Statistical inference

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Examples continued

  • 26×25×24×...×2×1=4×1026 possible combinations
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Examples continued

  • 26×25×24×...×2×1=4×1026 possible combinations

  • Check 100M per second

  • 120,000,000,000 years of computational time

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The Course

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Course Toolkit

Course Website: sta199-f21-001.netlify.app

  • Central hub for the course!
  • Quick tour of the website

Sakai sakai.duke.edu

  • Gradebook, quizzes

Slack: https://sta199-001-f21.slack.com/

  • Questions and general discussion

GitHub: https://github.com/sta199-f21

  • Distribute & work on assignments -- more on this later!
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Activities: Prepare, Practice, Perform

  • 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
  • Practice: practice applying statistical concepts and computing
    • Application Exercises (AE) during lecture
    • Graded for completion
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Activities: Prepare, Practice, Perform

  • 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

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Where to find help

  • Attend Office hours to meet with a member of the teaching team.

    • 10a-12p this Friday via zoom
    • Full office hours begin the week of August 30
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Where to find help

  • Attend Office hours to meet with a member of the teaching team.

    • 10a-12p this Friday via zoom
    • Full office hours begin the week of August 30
  • Use slack for general questions about course content and/or assignments, since other students may benefit from the response.

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Academic Resource Center

The Academic Resource Center (ARC) 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 or call 919-684-5917 to schedule an appointment.

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CAPS

Duke Counseling & Psychological Services (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

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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.
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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

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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, inclusive, 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 slack are available to ask questions
    • Email Professor Fisher if further arrangements needed
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Questions?

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Your turn!

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Create a GitHub account

Go to https://github.com/, and create an account (unless you already have one).

After you create your account, go to https://forms.gle/t4Z6jadPmyZhHDvq6 and enter your Duke email address (NETID@duke.edu) and GitHub username.

Some tips from Happy Git with R.

  • Incorporate your actual name!
  • Reuse your username from other contexts if you can, e. g., Twitter or Slack.
  • Pick a username you will be comfortable revealing to your future boss.
  • Be as unique as possible in as few characters as possible. Shorter is better than longer.
  • Make it timeless.
  • Avoid words with special meaning in programming (e.g. NA).
05:00
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Let's look at some data!

  • Let's take a look at the UN Votes analysis.
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For Thursday

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Meet the teaching team: Instructor

Prof. Alexander Fisher

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