Getting Started
This overview is designed to orient you to the class.
Programming with Data (Progdata) introduces on the principles of data science, including:
- data wrangling,
- modeling,
- visualization, and
- communication.
In this class, we link those principles to psychological methods and open science practices by emphasizing exploratory analyses and description, rather than confirmatory analyses and hypotheses. Through the semester, we will work our way through many topics covered in Wickham and Grolemund’s R for Data Science text and develop proficiency with tidyverse. This class emphasizes replication and reproducibility. Progdata is a practical skilled-based class and should be useful to students aiming for academia as well as those interested in industry. Applications of these methods can be applied to a full range of psychological areas, including perception (e.g, eye-tracking data), neuroscience (e.g., visualizing neural networks), and individual differences (e.g., personality assessment).
0.1 Big Ideas
This class covers the following broad five areas:
- Reproducibility;
- Replication;
- Robust Methods;
- Resplendent Visualizations; and
- R Programming.
0.2 Course Modality
The course is designed to be flexible to fit each of your unique schedules and situations. The course is scheduled to meet in person 2 days a week. As Covid-related precautions evolve, this schedule is subject to change. The class can function fully asynchronously and remotely if needed.
If you are sick, do not come to in person class meetings!
All assignments and projects for the class can be completed at your own pace and are due as part of your portfolio at the end of the semester.
0.2.1 Successful Asynchronous Learning
This video can help you to be a successful asynchronous learner.
Much of this information comes from Northeastern University’s Tips for Taking Online Classes.