Course Objectives: To understand the applications of Biostatics in Pharmacy. this subject deals with descriptive statistics, Graphics, Correlation, Regression, ANOVA, Introduction to Design of Experiments phase of Clinical trials and Observational and Experimental studies.
Couse Outcomes: Upon completion of the course the student shall be able to
>Know the various statistical techniques to solve statistical problems
>Know the operation of M.S. Excel, SPSS, R and MINITAB@, DoE(design of experiment)
>Appreciate statistical techniques in solving the problems
Unit -1
Introduction: Statistics, Biostatistics, Frequency Distribution
Measures of central tendency: Mean, Median, Mode- Pharmaceutical examples
Measures of dispersion: dispersion, Range, standard deviation, Pharmaceutical problems
Correlation: Definition, Karl Pearson's coefficient of correlation, Multiple correlation -Pharmaceuticals examples
Unit-2
Regression: Curve fitting by the methods of least squares, fitting the lines y= a+bx and x=a+by, Multiple regression, standard error of regression– Pharmaceutical Examples.
Sample, Population, large sample, small sample, Null hypothesis, alternative hypothesis, sampling,
essence of sampling, types of sampling, Error-I type, Error-II type, Standard error of mean (SEM) -
Pharmaceutical examples
Parametric test: t-test (Sample, Pooled or Unpaired and Paired), ANOVA, (One way and Two way),
Least Significance difference
UNIT – 3
Non-Parametric tests: Wilcoxon Rank Sum Test, Mann-Whitney U test, Kruskal-Wallis test, Friedman
Test
Introduction to Research: Need for research, Need for design of Experiments, Experiential Design
Technique, plagiarism
Graphs: Histogram, Pie Chart, Cubic Graph, response surface plot, Counter Plot graph.
Designing the methodology: Sample size determination and Power of a study, Report writing and
presentation of data, Protocol, Cohorts studies, Observational studies, Experimental studies, Designing
clinical trial, various phases.
Unit- 4
Introduction to Practical components of Industrial and Clinical Trials Problems: Statistical
Analysis Using Excel, SPSS, MINITAB®, DESIGN OF EXPERIMENTS, R - Online Statistical Software’s
to Industrial and Clinical trial approach
Unit- 5
Design and Analysis of experiments:
Factorial Design: Definition, 2power2
, 2power3 design. Advantage of factorial design
Response Surface methodology: Central composite design, Historical design, Optimization
Techniques