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Lecture 38

Conclusion

DATA 8

Spring 2020

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Announcements

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Data Science

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Why Data Science

  • Unprecedented access to data means that we can make new discoveries and more informed decisions
  • Computation is a powerful ally in data processing, visualization, prediction, and statistical inference
  • People can agree on evidence and measurement
  • Data and computation are everywhere: understanding and interpreting are more important than ever

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Limitations of Data Science

  • Evidence and measurements are critical ingredients for good decision-making
    • ...but they’re not enough by themselves!
  • Data science is a powerful complement to qualitative analysis
    • ...but it’s not a replacement!

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How to Analyze Data

Begin with a question from some domain, make reasonable assumptions about the data and a choice of methods.

Visualize, then quantify!

Perhaps the most important part: Interpretation of the results in the language of the domain, without statistical jargon.

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How Not to Analyze Data

Begin with a question from some domain, make reasonable assumptions about the data and a choice of methods.

Visualize, then quantify!

Perhaps the most important part: Interpretation of the results in the language of the domain, without statistical jargon.

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How to Analyze Data after Data 8

Begin with a question from some domain, make reasonable assumptions about the data and a choice of methods.

Visualize, then quantify! Do both using computation.

Perhaps the most important part: Interpretation of the results in the language of the domain, without statistical jargon.

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The Design of Data 8

  • Table manipulation using Python
  • Working with whole distributions, not just means
  • Decisions based on sampling: assessing models
  • Estimation based on resampling
  • Understanding sampling variability
  • Prediction

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Using Data Science to Understand COVID-19

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COVID-19: Remdesivir

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COVID-19: Remdesivir

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COVID-19: Santa Clara County

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COVID-19: Santa Clara County

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COVID-19: Santa Clara County

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COVID-19: Santa Clara County

Variance of a sample proportion

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COVID-19: Santa Clara County

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COVID-19: Nicotine and causality

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A Request

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Please fill out the course evaluations!

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What's Next?

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Guest Presentations

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data.berkeley.edu

Spring 2020

Student Opportunities

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Fall 2020 Connectors

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STAT 88

Prob and Stats in Data Science

UGBA 88

Data and Decision

PHYSICS 88

Data Science Applications in Physics

COMPSCI 88

Computational Structures

DATA 88-3

Economic Models

EPS 88

PyEarth: A Python Introduction to Earth Science

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Data Scholars

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For students who are

  • Low income
  • First generation college
  • Historically underrepresented

Foundations

Concurrent to Data 8

Pathways

Further technical

skill & career development

Discovery

Support for research

experiences

Data Scholars serves these populations to support diversity in the Data Science student community all the way through.

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DSEP Student Teams

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Peer Consulting

Hone your skills as an educator and data scientist by working with the Data Science Education Program

Help fellow undergrads with data research, academic work, and data science technology.

External Pedagogy

Create a national community of practice for institutions to work with and learn from each other.

Online

Learning

Help deliver Data 8 instruction via online cloud based instruction

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DSEP Student Teams

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Hone your skills as an educator and data scientist by working with the Data Science Education Program

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DSEP Student Teams

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Connector

Assistants

Modules

Hone your skills as an educator and data scientist by working with the Data Science Education Program

Help instructors of Data Science Connector courses deliver and teach material.

Create curriculum materials for Connectors, Data-Enabled Courses, or short explorations into DS (modules).

Human Context and Ethics

Integrate critical thinking about ethical issues in relation to technology into the Berkeley data science program and community.

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Discovery Student Researchers

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Be a student researcher in a program that connects students with hands-on data science research- non-profits, start-ups, institutions, etc. Students from underrepresented minority groups and first-time researchers receive priority.

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Data Science Peer Advising

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Peer Advisors share their diverse knowledge of and experiences with:

  • major courses
  • different data science major domain emphases
  • extracurriculars and student groups on campus
  • research opportunities
  • and various campus resources.

Peer Advisors work closely with the Data Science Advising Team and gain exposure to the ins-and-outs of a new and increasingly popular interdisciplinary major.

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How to Apply

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For more information,

check out our website at

Applications will re-open in July

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The Team

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Staff

  • GSIs
  • Tutors
  • Lab Assistants

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Thank you!