## Details of LS5103 (Autumn 2016)

Level: 5 |
Type: Theory |
Credits: 3.0 |

Course Code | Course Name | Instructor(s) |
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LS5103 |
Research Methodology |
Robert John Chandran, Supratim Datta |

Syllabus |
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Module 1: Basics of scientific methods, concept of hypothesis, experimental design, data interpretation and research ethics
1.1 Aim and motivation of research: Modes of knowledge acquisition, Basic elements of the Scientific method, Basic structure of the Scientific method 1.2 Asking questions, building hypothesis: Asking questions in science, understanding phenomenology, Hypothesis-driven and discovery-driven research. 1.3 Hypotheses building and testing: alternative and null hypotheses, experimentation, analysis and meta-analysis. 1.4 Designing experiments: Dependent and independent variables, Controls, Test of falsifiability, Reproducibility, Correlation and Causation. 1.5 Interpreting others data by reading published literature. 1.6: Ethics in Science: honesty, objectivity, ethics, and confidentiality, what is scientific misconduct? Instances of misconduct, plagiarism, fabrication and falsification of data, false attribution, case studies in research ethics. Module 2: Biostatistics 2.1 Role of statistics in the scientific methods. 2.2 Probability as an expression of uncertainty. Laws of Probability. 2.3 Probability distributions (discrete and continuous): Bernoulli, Binomial, Poisson, Normal. 2.4 Concept of Likelihood. Bayes theorem and Bayesian approach. 2.5 Exploratory data analyses for univariate, bivariate and multi-variate data. 2.6 Sampling distributions. Central Limit Theorem. 2.7 Fundamentals of frequentist Hypothesis testing. Type 1 and Type 2 errors. P-values. The pitfalls of significance testing and null hypotheses. 2.8 Expected and actual frequencies: Chi-square analyses. 2.9 Frameworks for statistical analyses. Bootstrap, Jackknife, Information theoretic methods. Bayesian Method and Inference. 2.10 Study design and sampling. 2.11 Linear models (Linear Regression and ANOVA). 2.12 Generalized linear models. 2.13 Statistical ethics. Module 3: Scientific papers, literature survey and grant writing 3.1 Structure of scientific papers: review and research article. 3.2 Thorough literature survey in a chosen area. 3.3 Writing a project proposal in a chosen area. 3.4 Defense of the project proposal (in form of a departmental seminar). Number of Credits: Total 3 credit course, 1 credit for each of the modules. Mode of evaluation: The first and second module will be evaluated by the respective course instructor(s). The third module will be evaluated by the respective PhD supervisor. |

References |
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#### Course Credit Options

Sl. No. | Programme | Semester No | Course Choice |
---|---|---|---|

1 | IP | 1 | Not Allowed |

2 | IP | 3 | Not Allowed |

3 | IP | 5 | Not Allowed |

4 | MR | 1 | Not Allowed |

5 | MR | 3 | Not Allowed |

6 | MS | 9 | Not Allowed |

7 | RS | 1 | Core |

8 | RS | 2 | Core |