- Attributes of science: Organization, crystallization and systematisation of knowledge; objectivity, impersonalism, abstractness in theory, practicality in application, reproducibility, universality, generalizability. Transpersonalization of experience -- collective and cumulative process; Organized skepticism.
- How science developed:
- Early (pre-Copernicus) period: Observation -- trial and error -- manipulation -- speculation; subjective approach; study and collection of facts; technology preceded theory. Greek science: Aristotle, Aristarcus, Archimedes, Euclid, Ptolemy. Indian tradition -- medicine, surgery, metallurgy, astronomy and mathematics.
- Post-rennaissance period: Radical change in the method of organization of knowledge. Skepticism -- critical review of common sense construction of theory about a class of facts -- theory to invention and application. Examination of theories; As example, Galileo's approach in mechanics and astronomy are to be dealt in detail.
- The development of the methods of science:
- Francis Bacon (truth from fact, experiment-observation-inference, inductive approach)
- Rene Descartes (science through reasoning -- mathematics called in. Deductive approach).
- Post-Newton: Success in prediction and explanation of natural phenomena, science in control, industrial revolution, classical mechanics, determinism and mechanical materialism.
- Organization of empirical observations into theory: Examples of Maxwell, Clausius, Carnot.
- Logic. Necessity of logic as the training for scientific thinking; Aristotelian principles of thinking -- formal logic, syllogism. Logic and critical thinking: inductive and deductive. Logical and mathematical consistency.
- Methodological aspects of modern science:
- Idealisation and abstraction in theory consistency test by mathematics
Confirmation by experiments. Examples.
- Proposition of hypothesis null hypothesis design of experiment to test hypothesis construction of theory (with examples of the methods followed by Rutherford, Madam Curie, etc.).
- Experiment: General principles of planning, designing and executing experiments for testing hypotheses, and for obtaining fresh data about phenomena. Ensuring objectivity in experiments: Eliminating experimenter bias, experimental group and control group, single blind and double blind tests. Estimation of experimental error. Importance of reporting experiments with error bars. How to report experiments in a way meaningful to fellow scientists. Maintenance of research data, records, and notebooks.
- Thought experiments: What are thought experiments? Why are they necessary? How to ensure that the inference is correct? Examples
- Models: Construction of models why development of model is necessary in science; pitfalls of modelling; examples.
- Poppers falsifiability criterion in proposing a theory. With examples.
- Causality: What is causality? Tests of causal connection between events and phenomena.
- Statistical inference from experimental data: How to check that an observation is not due to random chance but due to an actual physical process; z-statistics and T-statistics, confidence intervals.
- The art of science communication: Structure of scientific papers, M.Sc. and Ph.D. theses, common mistakes, citation and referencing, examples of papers written by eminent scientists.
- Confutation of pseudo-sciences: Application of the scientific method to refute and expose various belief systems the cases of astrology, palmistry, gems, paraphychology, supernormal powers.
- Research misconduct: Fabrication, distortion, plagiarism in proposing, performing, or reviewing research, or in reporting research results. Examples from the history of science.
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