Foundations in Data Science

A Curated Set of Modules and Activities for Behavioral Scientists

Author

Kimberly L. Henry

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Overview

This website serves as a comprehensive resource for students enrolled in PSY 652 (Research Methods in Psychology I) at Colorado State University, and for anyone aiming to build a strong foundation in applied data science. It is designed to equip you with the essential skills to effectively leverage data analytics in both your research and professional endeavors.

Learning Modules

Explore the structured and interactive Modules, each designed to address the unique needs of the social and behavioral sciences. These modules will equip you with the knowledge and skills necessary to navigate the complexities of data-driven research:

  1. Intro to the Tools: Get set up with R, RStudio and Quarto to master data analysis essentials.

  2. No Code Statistics: Review basic statistics.

  3. Data Visualization: Turn data into compelling visual narratives.

  4. Data Wrangling: Master data manipulation for analysis readiness.

  5. Basic Rules of Probability: Dive into basic probability concepts.

  6. Probability Distributions: Understand key statistical distributions.

  7. Descriptive Statistics with R: Use R for population estimates and summaries.

  8. Quantifying Uncertainty: Measure uncertainty in descriptive statistics.

  9. Confidence Intervals: Gain skills in forming confidence intervals.

  10. Simple Linear Regression: Analyze relationships between two variables.

  11. Multiple Linear Regression: Explore multiple predictors in regression analysis.

  12. Uncertainty in Regression: Assess uncertainty in regression estimates.

  13. Categorical Predictors: Manage categorical data in regression models.

  14. Moderation: Investigate how the effect of one variable may depend on another.

  15. Non-linear Relationships: Model complex data relationships.

  16. Hypothesis Testing: Test hypotheses using statistical models.

  17. Assumptions & Remediation: Address violations of statistical assumptions.

  18. Causal Inference: Learn what it takes to draw causal inferences from data.

Apply and Practice Activities

To reinforce your learning, each Module is supplemented with practical, hands-on activities. These exercises are designed to solidify your understanding and skills, providing you with opportunities to apply what you’ve learned to real-world data sets. A Posit Cloud work space dedicated to the course hosts the files necessary to explore all analyses in the Modules as well as complete the Apply and Practice Activities.

Lecture Activities and Slide Decks

Lecture slide decks (built with revealjs for Quarto) provide the content for each class period. These sessions build on the material in the Modules and incorporate WebR a magical interface for practicing with R in a web browser.

PSY 652 Course Details

Instructor

Teaching Assistant

Course details

  • Dates: August 19, 2024 - December 13, 2024
  • Days: Mondays (lecture), Wednesdays (lab)
  • Times: 9:30 - 12:10 (lecture), 3:30 - 4:45 (lab)
  • Location: 357 Behavioral Sciences Building