BP801T. RESEARCH METHODOLOGY (Theory)

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Unit-III: Introduction to Research and Data Presentation 

Unit-IV: Advanced Statistical Tools and Techniques

Unit-V: Design and Analysis of Experiments

Syllabus:

1. Fundamentals of Research

 Need for Research: Importance and scope in scientific inquiry and innovation.

 Need for the Design of Experiments: Significance of planning and structuring experiments effectively.

 Experimental Design Techniques: Basic principles and approaches.

 Plagiarism: Ethical considerations and tools for plagiarism detection.

2. Data Visualization and Graphical Representation

 Types of Graphs:

o Histogram

o Pie Chart

o Cubic Graph

o Response Surface Plot

o Contour Plot

3. Designing Research Methodology

 Sample Size Determination: Importance and techniques for estimating appropriate sample size.

 Power of a Study: Understanding statistical power and its implications.

 Report Writing and Data Presentation: Structuring scientific reports and presenting data effectively.

 Research Protocols: Writing and understanding study protocols.

4. Research Designs

 Cohort Studies: Definition, types, and examples.

 Observational Studies: Characteristics and applications.

 Experimental Studies: Overview and significance in research.

 Designing Clinical Trials:

o Overview of clinical trial design.

o Understanding various phases of clinical trials.

Unit-IV: Advanced Statistical Tools and Techniques

1. Blocking and Confounding

 Blocking: Purpose and methods to reduce variability.

 Confounding: Managing confounding factors in two-level factorial designs.

2. Regression Modeling

 Simple Regression Models: Hypothesis testing, assumptions, and applications.

 Multiple Regression Models: Advanced techniques and interpretation of results.

3. Practical Applications in Industrial and Clinical Trials

 Statistical Analysis Using Software:

o Excel

o SPSS

o MINITAB®

o R

 Design of Experiments for Industrial and Clinical Trials: Practical insights using online statistical tools.

Unit-V: Design and Analysis of Experiments

1. Factorial Design

 Definition and Fundamentals: Introduction to factorial experiments.

 Specific Designs:

o 2² Design

o 2³ Design

 Advantages of Factorial Design: Efficiency, interaction studies, and comprehensive analysis.

2. Response Surface Methodology (RSM)

 Overview: Applications in optimization studies.

 Design Techniques:

o Central Composite Design (CCD).

o Historical Design.

3. Optimization Techniques

 Strategies for experimental optimization to achieve desired outcomes.