BIOSTATISITCS AND RESEARCH METHODOLOGY
Teacher
Gyanaranjan Parida
Category
Core Courses
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Course Name : BIOSTATISITCS AND RESEARCH METHODOLOGY
Course Objectives
| CO | Statement | Mapping with PO |
| CO1 | To Know the operation of M.S. Excel, SPSS, R and MINITAB®, DoE (Design of Experiment) | PO2, PO3,
PO10,PO11 |
| CO2 | To Know the various statistical techniques to solve statistical problems | PO1, PO2,
PO5,PO10 |
| CO3 | Appreciate statistical techniques in solving the problems. | PO1, PO2,
PO5,PO10 |
Course 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
Session 3
Measures of central tendency: Median, Mode- Pharmaceutical examples
Session 4
Session 5
Measures of dispersion: Standard deviation, Pharmaceutical problems
LINK-https://youtu.be/Aydqi-mPdf4
PDFSD
Session 6
Correlation: Definition, Karl Pearson’s coefficient of correlation,
Session 7
Correlation: Multiple correlation - Pharmaceuticals examples
Session 8
Regression: Curve fitting by the method of least squares,
Session 9
Regression: Curve fitting by the method of least squares,
LINK-https://youtu.be/g1uNSL5CYbE
PDFRegression
Session 10
Regression: fitting the lines y= a + bx and x = a + by
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
Session 14
Probability: Sample, Population, large sample, small sample
PDFSAMPLING
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) ,
PDFT-TEST
Session 19
Session 20
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
PDFRESEARCH
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
https://www.youtube.com/watch?v=ihpn2glhp9I
pdf Blocking and confounding system for Two-level factorialsBlocking 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
https://www.youtube.com/watch?v=XONjN7mvosI
PDFMINITAB,DOE
Session 32
Introduction to Practical components of Industrial and Clinical Trials Problems: R - Online Statistical Software’s to Industrial and Clinical trial approach
https://www.youtube.com/watch?v=6trcmHIF1fk
PDFR-ONLINE
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 35
Response Surface Methodology: Historical design, Optimization Techniques
https://www.youtube.com/watch?v=Dt1bHJoj0zI
PDF Response Surface Methodology Historical design, Optimization Techniques
Session 36
Response Surface methodology: Central composite design
https://www.youtube.com/watch?v=f95B06bRfec
PDFCCD
Recommended Books (Latest edition):
1. Pharmaceutical statistics- Practical and clinical applications, Sanford Bolton, publisher Marcel Dekker Inc. NewYork.
2. Fundamental of Statistics – Himalaya Publishing House- S.C.Guptha
3. Design and Analysis of Experiments –PHI Learning Private Limited, R. Pannerselvam,
4. Design and Analysis of Experiments – Wiley Students Edition, Douglas and C. Montgomery
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