Introduction to Statistics and Data Analysis

(4 Credits)

An introduction to using statistics to understand the world around us. Formulating a hypothesis and collecting data, summarizing and visualizing, probability distributions, the central limit theorem and the normal distribution, hypothesis testing, confidence intervals, p-values, the power of an experiment, t-tests and comparing data sets, linear regression, machine learning methods. Assignments will use statistical software packages to analyze data, and throughout the semester, students will evaluate the implications and responsible practices of collecting and utilizing data. No previous experience with programming is necessary.