Module I:
1. Requirement for biostatistics, basics of hypothesis testing, trial design, sampling theory.
2.Descriptive statistics: Population and samples descriptive methods for categorical data descriptive methods for continuous data probability and probability distributions types of data frequency distribution measures of central tendency measures of variability kurtosis and skewness Z score.
Module II:
3. Inferential statistics: parameters estimating and comparing the mean of population.
Module III:
4. Hypothesis testing: basic concepts and steps testing normal distribution - Kolmogorov-Smimov test testing homogeneity of variance - Levene's test Z-tests dependent t-test, independent t-test, t-test as GLM, F-test, Chi-square test Type I and type II errors ANOVA, ANCOVA, factorial ANOVA, repeated-measures designs, mixed design ANOVA, post hoc procedures.
Module IV:
5. Non-parametric and distribution-free tests - Mann-Whitney test Wilcoxon signed-rank test, Wilcoxon signed rank sum test, Kruskal-Wallis test, Friedman's ANOVA.
Module V:
6. Correlation techniques: bivariate correlation - Pearson's correlation coefficient, Spearman's correlation coefficient Partial correlation regression - method of least squares, assessing goodness of fit multiple regression. Experimental design and clinical trials.

1. To impart training on basic biostatistics concepts and learn the use of various statistical tools for biomedical data analysis.

2. To identify appropriate bio-statistical tools for use in biological data analysis.

3. To understand concepts related to experimental design for hypothesis testing.

1. Identify and categorise different types of biological data.
2. Gain in-depth understanding of statistical concepts and their application towards biostatistics.
3. Understand and apply different types of hypothesis testing methods depending on experimental design.
4. Understand and apply different tools for understanding the inter-relationships between different variables in a biological system and predict their impact on the factor under study.
5. Learn modern methods and tools for practical application of biomedical, pharmaceutical data analysis and hypothesis testing.

• Le CT, Introductory Biostatistics, Wiley-Interscience, USA , ISBN: 0-471-41816-1

• Glaser AN, High Yield Biostatistics, Lippincott Williams and Wilkins, USA , ISBN: 0-781-72242-X

• Geller NL, Advances in clinical trial biostatistics, Marcel Dekker Inc, USA , ISBN: 0-82479032-4

• Field A, Discovering statistics using SPSS, SAGE, USA , ISBN: 978-1-84787-936-6