Trace analysis: definitions, methods and problems. Sampling, storage and contamination. Quality control. Random and systematic errors; statistical treatment of data. Accuracy and precision. Signal/noise ratio. Sensitivity and detection limits. Choice of methods for trace analysis.
Units, dimensions, exponentials and logarithms:
Decimal places and significant figures. Units and dimensions: SI units, dimensional analysis. Manipulation of exponentials and logarithms. Power laws. Exponential decay and half-life. Beer-Lambert law, Arrhenius equation, Boltzmann distribution, Gaussian functions.
Balancing chemical equations. Amount of substance, molar quantities, concentration and volumetric calculations, gravimetric analysis, gas pressures and volumes.
Equilibrium calculations, strong and weak electrolytes. pH, acid-base equilibria, buffer solutions. Solubility. Chemical kinetics: reaction rates, rate constants and orders of reaction.
Probability and Statistics:
Elementary probability, probability spaces, Venn diagrams, independence, mutual exclusion, expectation. Quantitative treatment of the effect of evidence: Bayes’ Theorem and conditional probability Samples and populations, mean, standard deviation, moments, standard error. Probability distributions: binomial, normal, poisson. Limiting cases. Use of normal tables. Significance testing and confidence limits. Hypothesis testing. The chi-squared test. A brief look at probability-based arguments used by expert witnesses, recent controversies and challenged convictions. Regression and correlation
Analysis of alkaloids by HPLC
Accelerant analysis by gas chromatography
Analysis of metal cartridge cases and counterfeit coins using X-ray fluorescence spectroscopy
Determination of copper by atomic absorption spectroscopy
Quantifying substances in a mixture using UV-visible spectroscopy
Isolation & purification of caffeine from tea leaves
This module appears in the following module collections.
24 hours of lectures, 5 hours of examples classes, 18 hours of laboratory sessions.
This is not available as a wild module.
Method of assessment
Examination 60%; Coursework 40%
P. Monk & L. J. Munro “Maths for Chemistry” 2nd edition (Oxford, 2010) ISBN 0199541299 S. K. Scott, “Workbooks in Chemistry – Beginning Mathematics for Chemistry” (Oxford, 1995). ISBN 0198559305
J. N. Miller and J. C. Miller, “Statistics and chemometrics for analytical chemistry”, 6th edition (Pearson Prentice Hall 2010), ISBN: 0273730428
D. Lucy “Introduction to statistics for forensic scientists”, (Wiley, 2005) ISBN 0 47 002201 9
M. R. Spiegel, “Schaum’s outline of probability and statistics” 4th edition (McGraw Hill, 2013) ISBN 9780071795579
D. Rowntree “Statistics without tears”, (Penguin, 2000) ISBN: 0 14 013632 0. It’s non-mathematical and excellent for getting a grasp of concepts.
See the library reading list for this module (Canterbury)
Knowledge and understanding of:Core and foundation scientific physical and chemical concepts, terminology, theory, units, conventions, and laboratory methods in relation to forensic science and the chemical sciences.
Areas of chemistry as applied to forensic analysis.
Numeracy (including data analysis and statistics).
Ability to demonstrate knowledge and understanding of essential facts, concepts, principles and theories relating to the subject and to apply such knowledge and understanding to the solution of qualitative and quantitative problems.
Ability to recognise and analyse problems and plan strategies for their solution by the evaluation, interpretation and synthesis of scientific information and data.
Ability to recognise and implement good measurement science and practice and commonly used forensic laboratory techniques.
Skills in the safe handling of chemical materials, taking into account their physical and chemical properties, including any specific hazards associated with their use and to risk assess such hazards.
Skills required for the conduct of standard laboratory procedures involved in analytical work, and in the operation of standard instrumentation used in analysis and separation in forensic and chemical sciences.
Ability to interpret and explain data derived from laboratory observations and measurements in terms of their underlying significance and the theory underpinning them, including an assessment of limits of accuracy.
Problem-solving skills, relating to qualitative and quantitative information, extending to situations where evaluations have to be made on the basis of limited information.
Numeracy and computational skills, including such aspects as error analysis, order-of-magnitude estimations, correct use of units and modes of data presentation.
Information-retrieval skills, in relation to primary and secondary information sources, including information retrieval through on-line computer searches.
Information-technology skills such as word-processing and spreadsheet use, data-logging and storage, Internet communication, etc.
Time-management and organisational skills, as evidenced by the ability to plan and implement efficient and effective modes of working).
Generic skills needed for students to undertake further training of a professional nature.
Study skills needed for continuing professional development and preparation for employment.
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Credit level 5. Intermediate level module usually taken in Stage 2 of an undergraduate degree.
- ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
- The named convenor is the convenor for the current academic session.
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