In this course, we will focus on developing the statistical skills needed to answer questions by collecting data, designing experimental studies, and analyzing large publicly available datasets. The skills learned will also help students to be critical consumers of statistical results. We will use a variety of datasets to develop skills in data management, analysis and effective presentation of results. Emphasis will be placed on gaining a solid conceptual understanding of the big ideas in statistics, a deep working knowledge of the main statistical tests and practical skills for conducting data analysis in a statistical software package called R. We will use R to do all computational and graphical aspects of data analysis and visualization and there will be minimal use of formulas in this course. Key statistical tests covered will include randomization simulations, chi-square, ANOVA, and linear and logistic regression.
Statistics for Data Analysis (MAT4216.01)
Josef Mundt
Prerequisites: A prior math or lab science course or permission of the instructor.
Credits: 4
M 6:30pm - 8:30pm; Th 6:30pm - 8:30pm
Maximum Enrollment: 12
Course Frequency:
This course is categorized as 4000, All courses, Environment, Four Credit, Josef Mundt, Mathematics, Monday and/or Thursday Afternoons, and tagged analyzing, data, Data analysis, graphs, investigating, presenting results, programming, Research, statistics.
Credits: 4
M 6:30pm - 8:30pm; Th 6:30pm - 8:30pm
Maximum Enrollment: 12
Course Frequency:
This course is categorized as 4000, All courses, Environment, Four Credit, Josef Mundt, Mathematics, Monday and/or Thursday Afternoons, and tagged analyzing, data, Data analysis, graphs, investigating, presenting results, programming, Research, statistics.