BIST-500-01 Conceptual Introduction to Biostatistics

Faculty:

Tractenberg, Rochelle

Provides a basic foundation for current and future thinking in terms of practical aspects of statistics/biostatistics. The course is
designed for the 'non-major' – that is, it is not intended to make students into statisticians. Part of the purpose of this course is to make the student aware of the complexities of the relationships between biostatistics and clinical research, particularly as they pertain to decision making. Students will learn to seek the rationale that other investigators give for their choices – and students will begin to incorporate these elements into their own writing about their own research. In the process, students may lose a sense of certainty about what one should do to "best" analyze their own data, but they will gain an appreciation for the logic and judgment required to select an appropriate inference test. This course provides students a scientifically-oriented perspective on the types of information that an expert statistician has (descriptive statistics, 1- and 2- sample means comparisons, measures of association and agreement, simple linear and multiple linear/logistic regressions). This is reflected in an ability to reason and justify, as well as to consider and interpret, their own work as well as the work of other researchers. The course focuses on conceptual understanding and not memorization of the formulae or calculus that proves or supports inferential analysis. The goal is to improve students' conceptual understanding of the differences and similarities in the inference tests, as well as how decision-making on the basis of analytic results is, and is not,
supported by the data at hand. Assessments target articulation of
arguments and decisions involving, or based on, fundamental aspects of
biostatistics in the context of research.

Credits: 3

Prerequisites: None

BIST-500-02 Issues and Considerations in Experimental Design

Faculty:

Tractenberg, Rochelle

This course focuses on the philosophical and analytic elements of clinical research (experimental) design. Students will focus on selecting the best outcomes, designing the most powerful experiments, and promoting the reproducibility of their results. General experimental designs, including ANOVA and ANCOVA, will be covered after discussion of the philosophical attributes of the hypothesis test and scientific method; motivations for proposing an experiment; consideration of the selection/evaluation of outcome measures; and drawing conclusions from/describing the results of carefully designed research. Assessments will focus students' attention on the design and analytic elements in published work in their areas of interest, with special attention to understanding the p-value and its role in decision making, (subsequent) experimental design, and the development of new knowledge.

Credits: 3

Prerequisites: None

Other academic years
There is information about this course number in other academic years:

• 2008-2009 Fall and Spring
• 2010-2011 Fall and Spring
• 2012-2013 Fall and Spring
• 2013-2014 Fall and Spring

More information
Look for this course in the schedule of classes.

The academic department web site for this program may provide other details about this course.