BM5033 Statistical Inference Methods in Bioengineering

Course details

Course contents

Experimental observations in biomedical engineering and clinical trials often contain a degree of error and uncertainty. The objective of this course is to familiarise students with different statistical tools to understand, describe and analyse these uncertainties and help in better experimental design. The topics covered in the course will also be demonstrated in the lab component of the course using Python or R. Even though the course does not have any pre-requisite students are expected to be comfortable with numbers. The tentative course contents are

  • Data types and their representation, descriptive statistics, measures of variability
  • CLT, Types of errors, Sample vs population,
  • Hypothesis testing, p-value, statistical power and sample size
  • t-test, chi-square test, ANOVA, non-parametric tests, normality test
  • Statistics in clinical trials - Contingency tables, sensitivity and specificity
  • linear regression, mixed modelling approaches, Logistic regression

References

  • Biostatistical Analysis by Jerrold Zar
  • Medical Statistics by Kirkwood and Sterne

Problem sets

  • To be uploaded

Reading materials

Python/R scripts, datasets etc.

Course logistics and policies

Some suggestions