BIOSTATISITCS AND RESEARCH METHODOLOGY (Theory)

Teacher

Dr.Amulyaratna Behera

Category

Core Courses

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Course Name : BIOSTATISITCS AND RESEARCH METHODOLOGY

Code(Credit) : BPHT4201 (4-0-0)

Course Objectives

• Know the operation of M.S. Excel, SPSS, R, and MINITAB ®, DoE (Design of Experiment)

• Know the various statistical techniques to solve statistical problems

• Appreciate statistical techniques in solving the problems.

Learning Outcomes

  • To understand the applications of Biostatics in Pharmacy.
  • To deal with descriptive statistics, Graphics, Correlation, Regression, logistic regression Probability theory, Sampling technique, Parametric tests, Non Parametric tests, ANOVA,
  • Introduction to Design of Experiments, Phases of Clinical trials and Observational and Experimental studies, SPSS, R, and MINITAB statistical software’s, analyzing the statistical data using Excel

Course Syllabus

Module-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 correlations - Pharmaceuticals examples

Module-2

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, the essence of sampling, types of sampling, Error-I type, Error-II type, Standard error of the mean (SEM) - Pharmaceutical examples
Parametric test: t-test(Sample, Pooled or Unpaired and Paired), ANOVA, (One way and Two way), Least Significance difference

Module-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 the 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

Module-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

Module-5

Design and Analysis of experiments:
Factorial Design: Definition, 2^2, 2^3design. Advantage of factorial design
Response Surface methodology: Central composite design, Historical design, Optimization Techniques

Session Plan

Session 1

Introduction: Statistics, Biostatistics, Frequency distribution

Session 2

Measures of central tendency: Mean,

Session 3

Measures of central tendency: Median, Mode- Pharmaceutical examples

LINK-https://youtu.be/knzrbZ4wWQY

Session 4

Measures of dispersion: Dispersion, Range,

LINK-https://youtu.be/AMTivCkMlFI

Session 5

Measures of dispersion: Standard deviation, Pharmaceutical problems

LINK-https://youtu.be/Aydqi-mPdf4

Session 6

Correlation: Definition, Karl Pearson’s coefficient of correlation,

LINK-https://youtu.be/z6Wbb3GeT5w

Session 7

Correlation: Multiple correlation - Pharmaceuticals examples

LINK-https://youtu.be/z6Wbb3GeT5w

Session 8

Regression: Curve fitting by the method of least squares,

LINK-https://youtu.be/GSw1a0yyLSo

Session 9

Regression: Curve fitting by the method of least squares,

LINK-https://youtu.be/g1uNSL5CYbE

Session 10

Regression: fitting the lines y= a + bx and x = a + by

LINK-https://youtu.be/knESk87ydxw

Session 11

Regression:Multiple regression, standard error of regression– Pharmaceutical Examples

Session 12

Probability:Definition of probability, Binomial distribution

Session 13

Probability: Normal distribution, Poisson’s distribution, properties - problems

LINK-https://youtu.be/hfBeF8jdO6U

https://youtu.be/VIH1DL77TN4

Session 14

Probability: Sample, Population, large sample, small sample

Session 15

Probability: Null hypothesis, alternative hypothesis

Session 16

Probability: sampling, essence of sampling, types of sampling, Error-I type, Error-II type

Session 17

Probability: Standard error of mean (SEM) - Pharmaceutical examples

Session 18

Parametric test: t-test(Sample, Pooled or Unpaired and Paired) ,

Session 19

Parametric test: ANOVA, (One way and Two way),

Session 20

Parametric test: Least Significance difference

Session 21

Non Parametric tests: Wilcoxon Rank Sum Test, Mann-Whitney U test

Session 22

Non Parametric tests: Kruskal-Wallis test, Friedman Test

Session 23

Introduction to Research: Need for research, Need for the design of Experiments, Experiential Design Technique, plagiarism

Session 24

Graphs: Histogram, Pie Chart, Cubic Graph, response surface plot, Counter Plot graph

Session 25

Designing the methodology: Sample size determination and Power of a study

Session 26

Designing the methodology: Report writing and presentation of data, Protocol

Session 27

Designing the methodology: Cohorts studies, Observational studies, Experimental studies, Designing clinical trial, various phases.

Session 28

Blocking and confounding system for Two-level factorials

Session 29

Regression modeling: Hypothesis testing in Simple and Multiple regression models

Session 30

Introduction to Practical components of Industrial and Clinical Trials Problems: Statistical Analysis Using Excel, SPSS

Session 31

Introduction to Practical components of Industrial and Clinical Trials Problems: MINITAB®, DESIGN OF EXPERIMENTS

Session 32

Introduction to Practical components of Industrial and Clinical Trials Problems: R - Online Statistical Software’s to Industrial and Clinical trial approach

Session 33

Design and Analysis of experiments: Factorial Design: Definition, 2^2, 2^3design

Session 34

Design and Analysis of experiments: Advantage of factorial design

Session 36

Response Surface Methodology: Historical design, Optimization Techniques

Session 35

Response Surface methodology: Central composite design

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