Data Science Course
Bill Perry
This course will serve as an introduction to reproducible data science and analysis using R. Specifically the goal is to introduce students to all facets of managing a research project with an emphasis on:
- Developing questions fro observations, hypotheses, and predictions for testing statistically
- Designing data workflows with data entry, curation, QA/QC, and cleaning
- Using a controlled vocabulary and organized project structure and documenting the metadata for the project
- Importing data into R and doing calculations and transformations
- Visualizing data using ggplot
- Understanding how to decide on statistical tests that are appropriate
- Descriptive Statistics
- T-Tests
- Regressions.
- Analysis of Variance.
- Analyzing Frequencies.
In the main webpage I have provided links to all the information you will need:
- links to readings that should be read prior to class
- powerpoint lectures that should be reviewed prior to class
- in-class activities that will actively cover the materials in the powerpoints
- weekly homework to do the in class activities on your own using different data