# Syllabus | BIOSTATISITCS AND RESEARCH METHODOLOGY THEORY | B. Pharmacy

 Course:  B Pharmacy          Semester: 8th   /4th Year Name of the Subject           BIOSTATISITCS AND RESEARCH METHODOLOGY         THEORY Subject Code: BP801T S. No. Contents of the Topics Domain Time(Hrs) 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 Nice to Know   Must Know 10 2 Hours Regression: Curve fitting by the method of least squares, fitting the lines y= a + bx and x = a + by, Multiple regression, standard error of regression– Pharmaceutical Examples Probability:Definition of probability, Binomial distribution, Normal distribution, Poisson’s distribution, properties – problems,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 Must Know   Must Know   Must Know 10 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 Must Know   Must Know   Must Know   Nice to Know   Must Know 10 4 Blocking and confounding system for Two-level factorials Regression modeling: Hypothesis testing in Simple and Multiple regression models 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 Nice to Know   Must know   Nice to Know 8 5 Design and Analysis of experiments: Factorial Design: Definition, 22, 23design. Advantage of factorial design Response Surface methodology: Central composite design, Historical design, Optimization Techniques Nice to know   Must know 7