Week 1: Chemical stoichiometry, parameters to define concentration of chemicals (normality, molarity, molality, mole-fractions, parts-per million), analytical concentration and equilibrium concentrations, p-value of concentration
Week 2: Measurements and its statistical analyses (definition of mean, median, mode, variance, standard deviation, standard error, accuracy, precision), need for performing replicates/repeats,reproducibility
Week 3: Classification and sources of errors, error propagation, scientific reporting data (significant figures), error curves
Week 4: Hypothesis validation (null hypothesis, confidence levels, confidence intervals, one-tail test, two-tail test, use of statistical tables such as z-table, t-table, F-table, identifying outliers in data with Q-test)
Week 5: Sampling, fitting and analysis of data (linear regression, single factor analysis of variance, least-significant difference).
Week 6: Software-based data analysis (linear and non-linear regression)
Week 7: Examples of data fitting and analysis (application to rate kinetics, gradient mixing, biomolecular folding)
Week 8: Sample preparation: concept of standards (primary and secondary), traditional methods of analysis (gravimetric, volumetric, potentiometric methods)
Week 9: Analytical separations (solvent extraction, chemical precipitation, chromatography, types of chromatography – size exclusion, ion exchange, affinity, gas, high pressure liquid chromatography, field-flow fractionation)
Week 10: Theoretical basis of chromatography (concept of plates, theoretical plate height, plate count, resolution, retention time, retention factor, selectivity factor)
Week 11: Differences between rate theory and plate theory
Week 12: Protocols with video demonstration of separation techniques
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