Introduction to statistics and study design:
Introduction tostatistics, data, variables, types of data, tabular, graphical andpictorial representation of data. Significance of statistics tobiological problems, experimental studies; randomized controlled studies, historically controlled studies, cross over,factorial design, cluster design, randomized; complete, block,stratified design, biases, analysis and interpretation
Descriptive statistics and Observational study design:
Typesof variables, measure of spread, logarithmic transformations,multivariate data. Basics of study design, cohort studies, casecontrolstudies, outcomes, odd ratio and relative risks.Principles of statistical inference: Parameter estimation,hypothesis testing. Statistical inference on categoricalvariables; categorical data, binomial distribution, normaldistribution, sample size estimation
Comparison of means:
Test statistics; t-test, F distribution,independent and dependentsample comparison, WilcoxonSigned Rank Test, Wilcoxon Mann-Whitney Test, ANOVA.Correlation and simple linear regression: Introduction, KarlPearson correlation coefficient, Spearman Rank correlation coefficient, simple linear regression, regression model fit,inferences from the regression model, ANOVA tables forregression.
Multiple linear regression and linear models:
Introduction, Multiple linear regression model, ANOVA tablefor multiple linear regression model, assessing model fit,polynomials and interactions. One-way and Two-way ANOVA tables, F-tests. Algorithm and implementation usingnumerical methods with case studies
Design and analysis of experiments:
Random block design,multiple sources of variation, correlated data and randomeffects regression, model fitting. Completely randomizeddesign, stratified design. Biological study designs.Optimization strategies with case studies.
Statistics in microarray, genome mapping and bioinformatics:
Types of microarray, objectives of the study, experimentaldesigns for micro array studies, microarray analysis,interpretation, validation and microarray informatics. Genome mapping, discrete sequence matching, programs formapping sequences with case studies