Updates
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Introduction to Data Science, https://www.idsucla.org
This website was last updated on May 9, 2024.
Changes that have been made to version 6.0
All Units
- Labs now also have text which direct students to complete tasks within the RStudio/Posit interface in blue font
- GPS no longer reports precise location
- There are anonymized datasets available for the Food Habits, Personality Colors, and Time Use (unformatted) Campaigns. They can be accessed by running the following code:
extra_data('food_ids') extra_data('color_ids') extra_data('timeuse_ids')
Unit 1
- Food Habits and Time Use campaign questions, in the campaign guidelines, have been modified for clarity
- Lesson 1: LMR_1.1 changed "Facebook" to "TikTok"
- Lesson 14: updated LMR_1.16 with new data/color palette
- Lesson 17: updated plots and cleaned up formatting on LMR_118
- Lab 1B has more clarification on options/arguments
- Labs 1C and 1F now have embedded videos to help guide students
- Lab 1D has more explanation about filtering and the assignment operator
Unit 2
- Stress/Chill campaign questions have been modified for clarity (and picture question has been removed)
Unit 3
Unit 4
- Section 1 is now Campaigns and Community where we set the stage for the End of Unit Project (also updated)
- Section 2 has been rehauled to improve the flow for the lessons on linear regression
- Section 2 also caps off with non-linear models with Lesson 13: Improving your Model (previously Lesson 14)
- Section 3 is now Piecing it Together with only the two lessons on multivariable regression
- The lessons in Section 4 have been slightly rearranged - part of Lesson 17 was moved to Lesson 16 for better building of concepts.
- Lesson 18: the LMR was modified for clarity. We also added instructions for the k-means clustering app.
- The End of Unit Project is student choice around a community issue
- Unit 4 Assessments have been updated (access through the Documents tool on Portal) - link to lungs data and solutions.
- Lab 4D lab solutions, MSE for 2nd variable changed to use y-variable,
critics_rating
, in residual calculation/code