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- Introduction to Probability and Data (began in April 2016)
- Inferential Statistics (begins in May 2016)
- Linear Regression and Modeling (begins in June 2016)
- Bayesian Statistics (begins in July 2016) A completely new course, with additional faculty!
- Statistics Capstone Project (August 2016) (for learners who have passed the 4 previous courses, and earned certificate)

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The goals of this course are as follows:

- Recognize the importance of data collection, identify limitations in data collection methods, and determine how they affect the scope of inference.
- Use statistical software (R) to summarize data numerically and visually, and to perform data analysis.
- Have a conceptual understanding of the unified nature of statistical inference.
- Apply estimation and testing methods (confidence intervals and hypothesis tests) to analyze single variables and the relationship between two variables in order to understand natural phenomena and make data-based decisions.
- Model and investigate relationships between two or more variables within a regression framework.
- Interpret results correctly, effectively, and in context without relying on statistical jargon.
- Critique data-based claims and evaluate data-based decisions.
- Complete a research project that employs simple statistical inference and modeling techniques.