Provides students with the fundamental principles of experimental design, statistical and exploratory data analysis and visualization, emphasizing research related to human health and clinical settings. Statistical topics include descriptive statistics, hypothesis testing, analysis of variance, correlation, regression, chi-square test, and non-parametric methods.
COURSE LEARNING OUTCOMES
By the end of this course, students will be able to:
1. Explain the role of regression models, conduct and interpret inferential statistics and descriptive statistics.
2. Plan and design analyses relevant for life sciences, formulate Null- and Alternative hypotheses and appropriately test these using statistical software.
3. Read, interpret and understand analyses based on texts or statistical outputs.
4. Interact and collaborate with epidemiologists, scientists and statisticians.
Raimann, Jochen G. (2021, Spring), Syllabus, Introduction to Statistics: STAT 1021G, Stern College for Women, Yeshiva University.
*This is constructed from limited available data and may be imprecise.