This course introduces the ideas of data summary and visualization, probability, and statistics with applications to natural and social sciences and daily life. Topics include but not limited to: random variables, discrete and continuous probability distributions, sampling distributions, confidence intervals, hypothesis testing, analysis of variance, and linear regression. This course builds a foundation for statistical inference, machine learning, and data modeling.
The course will assume facility with using the internet and a personal computer. A portion of the course involves programming using RStudio or Posit Cloud, but prior coding experience is not required.
