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

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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

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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

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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

 

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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

 

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