17BT41 Biostatistics and Biomodeling syllabus for BT



A d v e r t i s e m e n t

Module-1 BASIC STATISTICS 10 hours

BASIC STATISTICS:

Histogram, Ogive curve, Pie Diagram. Measure of dispersion (range, quartile deviation, mean deviation and standard deviation, coefficient of variation), Skewness & kurtosis.

Module-2 BI-VARIATE DISTRIBUTION 10 hours

BI-VARIATE DISTRIBUTION:

Correlation, rank correlation and regression analysis (simple and linear) curve fitting (linear, non-linear and exponential).

Module-3 PROBABILITY 10 hours

PROBABILITY:

Axioms, conditional probability, Bayes rule, Genetic Applications of Probability, Hardy - Weinberg law, Wahlund's Principle, Forensic probability determination, Likelihood of paternity, Estimation of probabilities for multi-locus/ allele finger print systems. Random variables- Discrete and Continuous Probability distribution, Mathematical expectations.

Module-4 PROBABILITY DISTRIBUTIONS 10 hours

PROBABILITY DISTRIBUTIONS:

Discrete probability distributions- Binomial, Poisson, normal, exponential derivations. Central limit theorem. T distributions.

Module-5 STATISTICAL INFERENCE 10 hours

STATISTICAL INFERENCE:

Estimation theory and testing of hypothesis, point estimation, interval estimation, sample size determination, parametric and non-parametric distributions -F-test, Chi Squared distribution, and goodness of fit test analysis of variance (one-way classifications). Randomization, random assignments, single and double blind experiments. Case studies of statistical designs of biological experiments. Microbial Growth in a Chemostat, Growth Equations of Microbial populations, Models of Commensalisms, Mutualism, Predation and Mutation. Volterra’s Model for n Interacting Species. Cigarette smoking, Lung cancer, epidemics.

 

Course outcomes:

After studying this course, students will be able to:

  • Fit a suitable curve for the tabulated data by the method of least squares, find correlation coefficients and analyze.
  • Apply different types of tests to test the hypothesis relating to small samples.
  • Appreciate the concepts of probability, distributions and various stochastic process.
  • Perform modeling and simulations experiments for select biological processes using appropriate data.

 

REFERENCE BOOKS

1. Statistical methods in Bioinformatics by Warren J. Ewens, Gregory R. Grant, Springer 2nd edition, 2006.

2. An Introduction to Biostatistics by P. S. S. Sundar Rao and J. Richard, Prentice Hall of India, publications, 4th edition, 2006.

3. Biostatistics: A foundation for Analysis in the Health sciences by Wayne W. Daniel, John 7th edition, 2000.

4. Fundamentals of Biostatistics by Veer BalaRastogi, Ane Books India.

 

TEXT BOOKS

1. Principles of Biostatistics by Marcello Pagano & Kimberlee G, Thompson Learning.

2. Introduction to Biostatistics by Ronadd N Forthofer and EunSul Lee, Academic Press.

3. Mathematical Models in Biology and Medicine by J.N.Kapur New Age International.

4. Introduction to Biostatistics by Ipsen, Feigl & Bancroft, Harper & Row, Publishers,NY.

5. Basic Biostatistics & its Applications by Animesh K Datta , New Central Book Agency.

6. Fundamentals of Biostatistics by P Hanumanth Rao and K Janardhan, IK Intl. Publishers.

7. Biostatistics by Rastogi V.B. Medtec 3rded , 2015

Last Updated: Tuesday, January 24, 2023