Analytical Science Course

Lesson 1 • Scientific Documentation and Reporting

Teaches laboratory notebook standards, data recording integrity, and structured report writing. Connects rigorous documentation to reproducibility and regulatory compliance.

Lesson 2 • The Analytical Science Discipline

Defines analytical science, its scope, and its role in industry, research, and regulation. Positions the field within the broader scientific landscape.

Lesson 3 • Error, Uncertainty, and Data Quality

Distinguishes systematic from random error and introduces uncertainty propagation. Learners learn to evaluate and report measurement reliability.

Lesson 4 • Laboratory Safety and Good Practice

Outlines chemical hazard classification, personal protective equipment, and waste disposal principles. Establishes safe working habits required throughout the course.

Lesson 1 • Descriptive Statistics for Analytical Data

Introduces mean, median, standard deviation, and variance as applied to replicate measurements. Provides the statistical language used throughout the course.

Lesson 2 • Hypothesis Testing and Significance

Applies t-tests, F-tests, and ANOVA to compare analytical results and methods. Learners determine whether observed differences are statistically meaningful.

Lesson 3 • Probability and Distributions

Covers normal and other relevant distributions and their role in analytical decision-making. Links probability concepts to confidence intervals and hypothesis testing.

Lesson 4 • Outlier Detection and Treatment

Presents Grubbs, Dixon, and other outlier tests appropriate for small analytical datasets. Teaches defensible decisions about retaining or rejecting suspect data points.

Lesson 1 • Dissolution and Digestion Methods

Covers acid digestion, fusion, and microwave-assisted dissolution for solid matrices. Learners match dissolution strategy to analyte and matrix type.

Lesson 2 • Liquid-Liquid and Solid-Phase Extraction

Introduces partitioning principles and sorbent-based extraction for isolating target analytes. Learners optimise extraction conditions for selectivity and recovery.

Lesson 3 • Sampling Theory and Strategy

Explains representative sampling, sample size calculations, and chain-of-custody requirements. Establishes that preparation quality begins before the laboratory.

Lesson 4 • Filtration, Centrifugation, and Cleanup

Describes mechanical separation methods used to remove particulates and matrix interferences. Connects cleanup steps to downstream instrument performance.

Lesson 1 • Principles of Titrimetric Analysis

Defines equivalence points, titration curves, and primary standards for solution standardisation. Establishes the theoretical basis for all titration types.

Lesson 2 • Acid-Base Titrations

Covers strong and weak acid-base systems, buffer regions, and pH indicator selection. Learners calculate analyte concentrations from titration data.

Lesson 3 • Complexometric and Redox Titrations

Introduces EDTA chelation titrations and oxidation-reduction titration methods. Expands quantitative capability to metal ions and redox-active analytes.

Lesson 4 • Precipitation Titrations

Covers argentometric methods and solubility product principles for halide determination. Learners apply Mohr, Volhard, and Fajans methods.

Lesson 1 • UV-Visible Spectrophotometry

Teaches instrument components, wavelength selection, and quantitative calibration using UV-Vis. Learners measure analyte concentrations in solution matrices.

Lesson 2 • Atomic Absorption and Emission Spectrometry

Covers flame and graphite furnace AAS, ICP-OES, and their use for trace metal determination. Learners select the appropriate technique based on sensitivity requirements.

Lesson 3 • Fundamentals of Spectroscopy

Covers electromagnetic radiation, energy transitions, and the interaction of light with matter. Provides the physical basis for all spectroscopic techniques in this chapter.

Lesson 4 • Infrared and Raman Spectroscopy

Explains molecular vibrations, IR absorption bands, and Raman scattering for structural identification. Learners interpret spectra to confirm compound identity.

Lesson 1 • Ion Chromatography and Size Exclusion

Covers ion-exchange mechanisms, suppressed conductivity detection, and size-based separation principles. Expands chromatographic capability to ionic and macromolecular analytes.

Lesson 2 • Gas Chromatography

Covers GC instrument components, stationary phase selection, and temperature programming for volatile analytes. Learners develop and troubleshoot GC methods.

Lesson 3 • High-Performance Liquid Chromatography

Introduces reversed-phase, normal-phase, and ion-pair HPLC modes with mobile phase optimisation. Learners develop gradient methods for complex mixtures.

Lesson 4 • Chromatographic Theory and Terminology

Defines retention, selectivity, efficiency, and resolution as the four pillars of chromatographic performance. Provides the vocabulary for all subsequent chromatography sections.

Lesson 1 • Spectral Interpretation

Teaches molecular ion identification, fragmentation patterns, and isotope ratio interpretation. Learners deduce molecular formulas and structural features from spectra.

Lesson 2 • Ionisation Techniques

Covers EI, ESI, APCI, and MALDI ionisation methods and their suitability for different analyte classes. Learners select ionisation modes based on analyte polarity and molecular weight.

Lesson 3 • GC-MS and LC-MS Coupling

Describes interface designs, scan versus selected-ion monitoring, and data acquisition strategies for hyphenated systems. Learners develop GC-MS and LC-MS methods for target analytes.

Lesson 4 • Tandem and High-Resolution MS

Introduces MS/MS fragmentation, triple-quadrupole MRM, and high-resolution accurate mass for complex matrices. Learners apply these techniques to trace-level and structural analysis.

Lesson 1 • Regulatory and Accreditation Frameworks

Surveys laboratory accreditation standards, good laboratory practice principles, and documentation requirements. Learners align their validation work with recognised quality frameworks.

Lesson 2 • Measurement Uncertainty Estimation

Applies the GUM framework to identify, quantify, and combine uncertainty sources in analytical methods. Learners produce a complete uncertainty budget for a chosen method.

Lesson 3 • Quality Control in the Laboratory

Introduces control charts, QC sample types, and acceptance criteria for routine analytical runs. Learners monitor method performance over time using statistical tools.

Lesson 4 • Calibration and Traceability

Covers reference material selection, calibration hierarchy, and metrological traceability to national standards. Connects calibration practice to defensible analytical results.