This course focuses on developing the statistical skills needed to design studies, analyze large datasets and to be a critical consumer of statistical results. We will design studies, collect and analyze data, and create effective presentations of results. We will also analyze large observational datasets. Emphasis will be placed on gaining a solid conceptual understanding of the main statistical tests and practical skills for conducting data analysis, with minimal use of formulas. We will be using statistical software called R (http://www.r-project.org/) for data visualization and analysis. We will focus on correlation, regression, logistic regression, ANOVA, and chi-square testing. While there are no formal prerequisites for the course, you should be willing to think deeply about concepts and to do the work required for class-based research projects.
Statistical Methods for Data Analysis (MAT2104.01)
Kathryn Montovan
Prerequisites: None.
Credits: 4
T 8:10am - 10:00am; F 8:10am - 10:00am
Maximum Enrollment: 18
Course Frequency:
This course is categorized as 2000, All courses, CAPA, Environment, Four Credit, Kathryn Montovan, Mathematics, and tagged analyze, collaboration, complex systems, computing, critical thinking, data analysis, data management, environment, environmental studies, experiment, Experimental, quantitative reasoning, R, research, statistics, technique, zombies.
Credits: 4
T 8:10am - 10:00am; F 8:10am - 10:00am
Maximum Enrollment: 18
Course Frequency:
This course is categorized as 2000, All courses, CAPA, Environment, Four Credit, Kathryn Montovan, Mathematics, and tagged analyze, collaboration, complex systems, computing, critical thinking, data analysis, data management, environment, environmental studies, experiment, Experimental, quantitative reasoning, R, research, statistics, technique, zombies.