Quantitative Methods in Chemistry

COURSE LAYOUT

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. Classification and sources of errors,error propagation, scientific reporting data (significant figures), error curves
Week 3 : 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 4 : Sampling, fitting and analysis of data (linear regression, single factor analysis of variance, least-significant difference)
Week 5 : Software-based data analysis (linear and non-linear regression)
Week 6 : Examples of data fitting and analysis (application to rate kinetics, gradient mixing,biomolecular folding)
Week 7 : Analytical separations (solvent extraction, chemical precipitation, various types of chromatography – size exclusion, ion exchange, affinity, gas, high pressure liquid chromatography, field-flow fractionation), Detectors in chromatography
Week 8 : Theoretical basis of chromatography (concept of plates, theoretical plate height,plate count, resolution, retention time, retention factor, selectivity factor),Differences between rate theory and plate theory