# Curriculum | 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 Unit Topic (Contents) Learning Objective ( By the end of lesson should be able to) Teaching Guidelines Methodology 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 By the end of lesson the student should be able to understand and explain Introduction of biostatics ·         Statistics ü  Introduction   ·         Measures of central tendency: ü  Mean ü  Median ü  Mode ü  Pharmaceutical problems ·         Measures of dispersion: ü  Dispersion ü  Range ü  Standard Deviation ü  Pharmaceutical Problems   ·         Correlation ü  Definition ü  Karl Pearson’s coefficient of    correlation ü  Multiple correlation ü  Pharmaceutical problems ü  Didactic Lecture   ü  Problem base assignments 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 Upon completion of this unit the student should be able to understand and explain Hours regression and parametric test ·         Regression ü  Definition ü  Curve Fitting method of least square ü  Multiple Regression ü  Standard error of regression ü  How to calculate Standard error regression ü  Pharmaceutical problems   ·         Probability ü  Definition ü  Binomial distribution ü  Normal distribution ü  Poisson’s distribution ü  Sample ü  Population ü  large sample ü  small sample ü  Null hypothesis ü  Alternative hypothesis Sampling ü  Types of sampling ü  Error-I type ü  Error-II type ü  Standard error of mean (SEM) ü   Pharmaceutical examples   Parametric test ü  t-test(Sample, Pooled or Unpaired and Paired) , ü  ANOVA, (One way and Two way), ü  Pharmaceutical calculations ü  Instructive ü  Case history   ü  Problem based power point presentations   ü  Problem based assignments 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 to understand and explain Nan parametric tests and introduction to research methodology ·         Non Parametric tests:   ü  Wilcoxon Rank Sum Test ü  Mann-Whitney U test ü  Kruskal-Wallis test ü  Friedman Test   ·         Research ü  Introduction ü  Need of research ü  Experimental design ü  Plagiarism   ·         Graphs How to make histogram, Pie Chart, Cubic Graph, response surface plot, Counter Plot graph     ·         Designing the methodology ü  Sample size Determination ü  Report writing ü  Presentation of data ü  Observational studies ü  Experimental studies ü  Designing clinical trial ü  Various phase ü  Preclinical phase ü  Phase I ü  Phase II ü  Phase III ü  Phase IV Didactic lectures through power point presentations   Tutorials   Seminars   Problem based assignments 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 the student should be able to explain regression modeling   Explain statistical softwares ·         To cover Blocking and confounding system for Two-level factorials ·         Regression modeling ü  Hypothesis testing ü  Multiple regression Models ·         Practical components of Industrial softwares ü  SPSS ü  MINITAB Didactic lectures   Power point presentations   Online statistical software handling presentations 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 able to  explain design and analysis of experimentations ·         Factorial Design ü  Definition ü  l22, 23design ü  Advantage of factorial design   ·         Response Surface methodology: ü  Centra composite design, ü  Historical design, ü  Optimization Techniques Power point presentations   Tutorials 7