Principles of Biostatistics
Basic concepts of biostatistics and their applications and interpretation. Topics include descriptive statistics, graphics, diagnostic tests, probability distributions, inference, regression, and life tables.
 Hours3.0 Credit, 3.0 Lecture, 0.0 Lab
Course Outcomes: 

Theoretical Basis

Understand the theoretical basis of biostatistics including types of data, data collection methods, data organization and graphic representation, use of probability distributions, basic understanding of probability theory, generation of statistical hypothesis, the nature of statistical error, underlying test assumptions, and the general principles of inferential links between populations and samples.

Data Execution

Execute the calculations or statistical tests covered during the semester on primary and/or secondary data.

Findings and Conclusions

Interpret the findings and draw appropriate conclusions for each statistical method and test covered during the semester.

Test Selection

Select an appropriate test (e.g., student t-test, chi-square) for a given data type and analysis problem from the materials covered during the semester.

Tool Application

Apply the tools acquired in this class to common situations (e.g., analysis of variance, logistic regression, linear regression, and survival analysis).

SAS Software

Apply SAS software for assessing biostatistical problems.