This course will comprise of 3 lab rotations, in which the students are expected to familiarize themselves with the research in the labs of their choice and learn various laboratory techniques. This exercise will also enable the students to select potential PhD mentor. In addition to this, there will be theory classes in the following format:\\
RESEARCH METHODOLOGY
- Introduction to the Scientific Method
- Aim and motivation of research
- Modes of knowledge acquisition
- Basic elements of the Scientific method
- Basic structure of the Scientific method
- Asking questions, building hypothesis
- Asking questions in science, understanding phenomenology
- Hypothesis-driven and discovery-driven research, building hypotheses: alternative and null hypotheses
- Testing hypotheses: experimentation, analysis and meta-analysis
- Designing experiments
- Dependent and independent variables
- Controls
- Test of falsifiability
- Reproducibility
- Correlation and Causation
- Interpreting others data: reading published literature
- Reading and writing paper in biology
- Structure of scientific papers: Aufbau and multi-foci
- Reading examples of Aufbau and multi-foci papers
- Ethics in Science
- Research ethics: honesty, objectivity, ethics, confidentiality etc.
- What is scientific misconduct?
- Instances of misconduct: plagiarism, fabrication and falsification of data, false attribution
- Case studies in research ethics
- BIOSTATISTICS MODULES
- Heads or Tails?
- Basics of probability
- Frequentist vs. Bayesian perspectives on probability (& Bayes Theorem)
- Central tendency & spread (mean, median, mode, quartiles)
- Basic distributions: Binomial, Poisson, Normal Distribution (& CLM)
- Testing for departures from Normality
- Lies Damn Lies & .
- Sample vs. Census
- Correlation ? Causation
- The Null Hypothesis & the logic of falsification
- P-values ? TRUTH
- Statistical Ethics
- The meaning of P
- Type I & Type II error
- Significance & Power & Effect size
- Confidence intervals
- Multiple testing: issues, correction (Bonferroni vs. FDA vs. Binomial Probability)
- Statistical Ethics
- Statistical methods I
- One sample z test
- t-Test
- ANOVA
- Statistical methods II
- Correlation
- Linear & Multiple Linear Regression
- Statistical Methods III
- Binomial (Logistic) regression
- Poisson Regression
- Statistical Methods IV
- Bootstrap
- Jackknife
- Randomization & Monte-Carlo
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