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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 to learn and apply statistical concepts.

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

Topics include:

  • R Programming
    • Accessing data
    • Generating output
    • Manipulating objects
    • Performing and generating statistical analyses
    • Creating statistical graphics
  • Statistics
    • Descriptive statistics
    • Probability
    • Hypothesis testing
    • Power and sample size
    • Correlation
    • Regression
    • Categorical data analysis
    • Design of experiments
    • Analysis of variance (ANOVA)

Practical experience:

  • Hands-on experiments and statistical analyses using R

Software: R, a free software environment for statistical computing and graphics, is used for this course.

Textbook: None.

Course typically offered: Online, quarterly.

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

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

Contact: For more information about this course, please contact

Course Number: CSE-41198
Credit: 3.00 unit(s)
Related Certificate Programs: Applied BioinformaticsR for Data Analytics

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