Quantitative Methods in Chemistry
- Offered bySwayam
Quantitative Methods in Chemistry at Swayam Overview
Duration | 8 weeks |
Mode of learning | Online |
Official Website | Go to Website |
Credential | Certificate |
Quantitative Methods in Chemistry at Swayam Highlights
- Earn a certificate from Swayam
- Learn from industry experts
Quantitative Methods in Chemistry at Swayam Course details
- For individuals who want to enhance their knowledge & skills in the field
- This course aims to train students towards appropriate scientific reporting of the experimental data and testing hypothesis using statistical analyses
- It emphasizes on reproducibility of experiments and the sources of “errors” during repetitions of experiments, how to quantify and minimize wherever feasible
- In the later part, it introduces the wide variety of separation techniques (for instance solvent extraction and chromatography etc.) employed for chemicals,polymers and biomolecules
- Basic introduction of instrumentation involved in these techniques will also be discussed
Quantitative Methods in Chemistry at Swayam Curriculum
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