Course Objectives:

• Develop a research workflow that is supportive of the scientific values of reproducibility, transparency, and collaboration.
• Organize a dataset for the purposes of statistical analysis by developing skills for importing data and data wrangling (munging).
• Create effective plots and figures to visually demonstrate the general trends, variations, and associations in any given dataset.
• Conduct and analyze linear and logistic regression models in R.
• Assess and address the assumptions of common statistical procedures used in psychological research including linear and logistic regressions.
  
• Use R, R Studio, Git, Github and additional Git Clients to effectively manage research workflow and work collaboratively with a peer on a data science project.
• Create and communicate results from a data science project using R Markdown and R Presentations.