## PY6010 - EXPERIMENTAL DESIGN AND BIOSTATISTICS (Syllabus) 2013-regulation Anna University

PY6010

EXPERIMENTAL DESIGN AND BIOSTATISTICS

LPTC

3003

OBJECTIVES:
• To introduce the fundamentals of statistics, logical application, and interpretation of statistical models. Emphasis will be placed on gaining a conceptual understanding of the statistical tests and their application to pharmaceutical research.
• To provide foundations on design of experiments and statistical analysis of experimental data obtained from laboratory and/or industrial processes.

UNIT I

9

Introduction: Definition of Bio-Statistics, Application of Bio-statistics, classification and sampling of data, objects of classification, frequency of distribution, methods of sampling, Tabulation of data, difference between Classification and Tabulation.

UNIT II

9

Measures of Central Tendency and Dispersion: Mean, median, mode, percentiles, range, variance, standard deviation, coefficient of variation measures skewness and kurtosis. Methods of sampling: Simple Random sampling with and without replacement. Sampling distribution and standard deviation of sample mean. Standard distributions: Binomial, Poisson, normal, exponential.

UNIT III

9

Correlation and regression: scatter plot, correlation coefficient, properties, rank correlation. Linear regression: Fitting of line and plane of regression. Analysis of Variance: ANOVA principle, assumptions of ANOVA, ANOVA of one way classified data, Analysis of 2 way classified data, non parametric tests, ANOVA and multiple regressions for biological data. Testing of Hypothesis: chi square test, test of fit, uses of chi square test.

UNIT IV

9

Design of experiments: Statistical principles in experimental design - blocking, complete randomization; Factorial design, optimization of pharmaceutical formulations Factor Eﬀect Analysis: Analysis of individual factor and interaction eﬀects; Response surface methodologies Advanced topics: Variable selection; Fractional factorial design; Robustness

UNIT V

9

Experimental design in clinical trials: Introduction, Principles of experimental design and analysis, parallel design, cross over design, split plot design, interim analysis. Monte carlo simulation and bootstrapping.

TOTAL : 45 PERIODS

OUTCOME:
The student will be able to understand the art of statistical data analysis combined with systematic approaches to experimental design.

TEXT BOOKS:
1. R.L. Mason, R.F. Gunst and J.L. Hess (2005). Statistical Design and Analysis of Experiments – with applications to engineering and science, 2nd edition, John Wiley & Sons Inc.
2. Z. R. Lazic (2006). Design of Experiments in Chemical Engineering: A Practical Guide. John Wiley & Sons Inc.
3. Pharmaceutical Statistics: Practical and clinical applications, Sanford Balton & Charles Bon, 4th edition, 2004, Marcel Dekker Inc, New York.

REFERENCES:
1. Pharmaceutical Experimental Design. Gareth A. Lewis, Didier Mathieu, Roger Phan-Tan- Luu. Marce l, Marcel Dekker, Inc. New York • Basel
2. D.C. Montgomery and G.C. Runger (2007). Applied Statistics and Probability for Engineers, 4th edition, John Wiley & Sons Inc.
3. Bernard Rosner, Fundamentals of Biostatistics, 5th Edition, Thomson Brooks/Cole, 2000.