Introduction to Statistics using R

Statistics allows us to collect, analyze, and interpret data. The R programming language is one of the most widely used tools for data analysis and statistical programming. Its easy-to-learn syntax, built-in statistical functions, and powerful graphing capabilities make it an ideal tool for learning and applying statistical concepts.

In this course, you will master the most widely used statistical methods while also learning to design efficient and informative studies, perform statistical analyses using R, and critique the statistical methods used in published studies. The emphasis is on concepts and applications, with ample opportunities for hands-on work. No prior knowledge of statistics or the R programming language is required.


Topics include:

R Programming

• Accessing data
• Manipulating objects
• Generating output
• Performing and generating statistical analyses
• Creating statistical graphics

• Causality and correlation
• Frequentist and Bayesian statistics
• Descriptive statistics
• Probability
• Hypothesis testing
• Confidence intervals
• Power and sample size
• Regression
• Model fitting
• Categorical data analysis
• Design of experiments

Practical experience:

• Hands-on experiments and statistical analyses using R

Software: R, a free software environment for statistical computing and graphics

Textbook: None

Course typically offered: Online, quarterly

Prerequisites: Knowledge of basic programming or Introduction to R Programming course is recommended.

Next Steps: Upon completion of this course, consider enrolling in other required coursework in the R for Data Analytics specialized certificate program

Contact: For more information about this course, please contact unex-techdata@ucsd.edu