Biostatistics and Design of Experiments

Biostatistics is the application of statistics to different topics in biology including medicine, pharmacy, public health science, agriculture and fishery. It involves the analysis of data from experiments; its interpretation and drawing conclusion from the results. It is very relevant to all UG and PG level degree programmes majoring in Biotechnology and allied fields as well as practicing scientists. It involves the application of statistical theory to real-world problems, the practice of designing and conducting biomedical experiments and clinical trials. Design of experiments is planning experimental strategy, screening a large number of parameters and selecting the important ones, determining the minimum number of experiments and deciding on the mode and manner in which experiments have to be conducted. The course encompasses topics such as distribution of data, sample size, tests of significance, data reduction, regression analysis, comparison of performance of drugs in clinical trials, design of experiments, screening and second order designs.

Introduction.
Experimental Design Strategy.
Data types : Binomial distribution.
Poisson Distribution.
Normal Distribution.
Standardized Normal Distribution/ t-distribution.
t-distribution/confidence interval.
Statistical tests.
t-Test.
t-Tests.
t- test.
F-tests.
F-tests contd.
ANOVA.
ANOVA Contd.
Anova Contd.
Anova contd.
Anova- Contd.
Anova-contd.
Anova- contd.
Normality test/ Odds ratio.
Chi square distribution.
Chi square distribution/test.
Chi square test.
Chi square test and Weibull Distribution.
Weibull Distribution.
Weibull distribution..
Non-parametric test.
Non parametric test/homogeneity of variance/beta distribution.
Exponential/hypergeometric distributions.
Hypergeometric/ Log norma distribution.
Design of experiments (DOE) - Introduction.
Factorial Design.
Full factorial design.
Fractional factorial design.
Other designs.
Second order designs.
Second order design.
Regression analysis.
Control charts.