Details of LS4202 (Spring 2017)

Level: 4 Type: Theory Credits: 3.0

Course CodeCourse NameInstructor(s)
LS4202 Biostatistics Robert John Chandran


  • Thermal Physics: Kinetic theory of gases. Derivation of the ideal gas laws based on kinetic theory. The first law of thermodynamics. Applications to ideal gas processes. Carnot cycle. The second law of thermodynamics. The concept of entropy.

  • Basics of Electromagnetism: Electrostatics - electric field and potential. Electric flux - analogy with fluid flow. Gauss law and its applications. Magnetism - Amperes law and applications. Faraday's law and electromagnetic induction.

  • Special Theory of Relativity: Einstein's postulates. The invariant interval. Lorentz boost (derivation not required). Phenomenological consequences. Redefinition of momentum. The mass energy relation.

  • The Nucleus: Nuclear reactions and decay. Basics of nuclear fission and fusion.


  • Introduction: the need for statistical analyses and models in biology: Testing relationships among biological/biophysical variables: regression and correlation. Univariate models.

  • Testing covariates and multiple variables: multiple linear regression.

  • Experimental Design and ANOVA: fixed effects, random effects, mixed effects models, interactions;

  • Multivariate analyses: multivariate data, multivariate normal distribution, principal components, ordination.

  • Cluster Analyses: distance function, UPGMA/average linkage clustering, construction of phylogenetic trees.

  • Non-parametric Methods: signed-rank test, Mann-Whitney test, Kruskal-Wallis test, rank correlation.

  • Teaching Methods Since the basic principles of probability and statistics are already covered in the Probability and Statistics course in the 4th Semester, this course will proceed straight to the topics mentioned above, focusing on the principles in brief, and illustrating the applications with numerous examples and exercises. In addition, there will also be invited guest lectures on specific topics.


  1. George W. Snedecor and William G. Cochran, Statistical Methods 8th Ed(1989)

  2. Robert R. Sokal and F. James Rohlf, Biometry: The Principles and Practices of Statistics in Biological Research (1994)

  3. Richard A. Johnson and Dean W. Wichern, Applied Multivariate Statistical Analysis (6th Edition) (2007)

  4. Nicholas J. Gotelli and Aaron M. Ellison, A Primer of Ecological Statistics. (2004)

  5. Brian S. Everitt, Sabine Landau, Morven Leese and Daniel Stahl, Cluster Analysis (Wiley Series in Probability and Statistics) (2011)

Course Credit Options

Sl. No.ProgrammeSemester NoCourse Choice
1 IP 2 Not Allowed
2 IP 4 Elective
3 IP 6 Not Allowed
4 MR 2 Not Allowed
5 MR 4 Not Allowed
6 MS 8 Core
7 RS 1 Elective
8 RS 2 Elective