Statistics I and II: Accelerated

Students will have the opportunity to learn basic parametric and non-parametric statistical methods to analyze real-world data. Many examples used in this program will relate to ecology and environmental studies, but any students are welcome to take this course to learn how to apply statistical methods to any type of data. Students will learn concepts and methods in Statistics I and II at an accelerated pace over the course of 10 weeks and also have the opportunity to apply methods to data of their choice. Concepts will include probability, basic summary statistics, and a suite of nonparametric and parametric statistical tests: Student’s t-tests, Chi-square tests, Analysis of Variance, Linear Regression, Correlation, Advanced ANOVA, classification and regression tree (CART) models, non-metric multidimensional scaling (NMDS) ordinations, and meta-analysis techniques. Students will learn to interpret findings, write about their results and create useful figures and tables. Students will complete weekly readings, weekly quizzes, and weekly statistics lab assignments. Final conceptual and practical exams will provide students opportunities to demonstrate knowledge gained. 

This program will be offered in both in-person and remote modalities. To be successful in this program, remote students should have a laptop (mac or PC) with reliable internet connection (a chromebook will not be sufficient - contact the faculty with questions). Lectures and statistics labs will be offered in-person, but video lectures will be provided for remote students, and scheduled video conferences for remote students will be available. The majority of the work in the program will be self-paced (meaning you could watch video lectures and complete lab assignments at your own pace or on your own schedule), but faculty will be available in-person to offer assistance during statistics labs. If students find themselves unable to participate in the in-person meetings due to living situations, care-giving obligations, economic disruption, health risk, or illness, they can work with faculty to complete the work remotely.